About Noise Reduction - Revision history

Jdc at 05:27, 13 June 2021

2021-06-13T05:27:41Z

Jdc: /* Denoising with Local adjustments */

2021-06-12T11:38:26Z

Denoising with Local adjustments

← Older revision		Revision as of 11:38, 12 June 2021
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	Depends on the individual image and whether or not there are uniform dark and/or light areas. If the image contains an almost perfectly uniform dark area, the background of the corresponding mask will be completely black (L = 0). If the dark area is not completely uniform this value will vary. The slider will progressively increase the action of the denoise curve between the dark or light threshold and the completely uniform area. Values less than 1 decrease the action of the curve.		Depends on the individual image and whether or not there are uniform dark and/or light areas. If the image contains an almost perfectly uniform dark area, the background of the corresponding mask will be completely black (L = 0). If the dark area is not completely uniform this value will vary. The slider will progressively increase the action of the denoise curve between the dark or light threshold and the completely uniform area. Values less than 1 decrease the action of the curve.

	====Edge detection - DCT" > Luma and chroma detail threshold (DCT f - uses Fourier transforms and wavelets)====		===="Edge detection - DCT" > Luma and chroma detail threshold (DCT f - uses Fourier transforms and wavelets)====

	This slider tries to take into account the edge effect of the original image in order to differentiate the action between uniform areas and areas with detail. Two algorithms are available (both from ART.)		This slider tries to take into account the edge effect of the original image in order to differentiate the action between uniform areas and areas with detail. Two algorithms are available (both from ART.)

Jdc at 11:33, 12 June 2021

2021-06-12T11:33:34Z

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DrSlony at 14:27, 28 May 2021

2021-05-28T14:27:04Z

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	<div class="pagetitle">Comparison of the ~~Rawtherapee~~ noise reduction tools</div>		<div class="pagetitle">Comparison of the RawTherapee noise reduction tools</div>

	==Preamble==		==Preamble==

	To put the Local Adjustments denoise tools into context, it is useful to summarize the other denoise tools available elsewhere in RT (Detail and Wavelets tabs) and to provide some additional information on the algorithms used. This information is complementary to the existing documentation, which can be found in the relevant sections of Rawpedia.		To put the Local Adjustments denoise tools into context, it is useful to summarize the other denoise tools available elsewhere in RawTherapee (Detail and Wavelets tabs) and to provide some additional information on the algorithms used. This information is complementary to the existing documentation, which can be found in the relevant sections of Rawpedia.

	Tools initially designed by Emil Martinec in 2012 located in "Ftblockdn.cc".		Tools initially designed by Emil Martinec in 2012 located in "Ftblockdn.cc".
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	==Improvements with "Non-local means" - also called patch-based denoise (Local Adjustments tab) february 2021==		==Improvements with "Non-local means" - also called patch-based denoise (Local Adjustments tab) february 2021==

	* this algorithm (origin Ipol 2014 [https://pdfs.semanticscholar.org/a262/269fa4b44b64d750c72fad3887f9d88817ce.pdf]) was ported to ART by Alberto Griggio and improved by Ingo Weirich, Jacques Desmis adapted it to ~~Rawtherapee~~.		* this algorithm (origin Ipol 2014 [https://pdfs.semanticscholar.org/a262/269fa4b44b64d750c72fad3887f9d88817ce.pdf]) was ported to ART by Alberto Griggio and improved by Ingo Weirich, Jacques Desmis adapted it to RawTherapee.

	* What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.		* What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.
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	* For chrominance noise, the first 4 levels are suitable for the noise which generates distributed colored pixels. For packets of noise (blotches), we can only get rid of these by going up to level 7.		* For chrominance noise, the first 4 levels are suitable for the noise which generates distributed colored pixels. For packets of noise (blotches), we can only get rid of these by going up to level 7.

	==Main characteristics of the various RT noise reduction tools==		==Main characteristics of the various RawTherapee noise reduction tools==

	===Noise Reduction (Detail tab)===		===Noise Reduction (Detail tab)===

DrSlony: DrSlony moved page Comparison of the 3 Rawtherapee noise reduction tools to About Noise Reduction

2021-05-28T14:12:48Z

DrSlony moved page Comparison of the 3 Rawtherapee noise reduction tools to About Noise Reduction

← Older revision	Revision as of 14:12, 28 May 2021
(No difference)

DrSlony: Formatting mostly

2021-05-28T14:11:02Z

Formatting mostly

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Jdc at 16:26, 5 February 2021

2021-02-05T16:26:58Z

← Older revision		Revision as of 16:26, 5 February 2021
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	* Tiling option.		* Tiling option.

	===Blur/Grain & Denoise (Local Adjustments tab) ~~+ Non-local means~~===		===Blur/Grain & Denoise (Local Adjustments tab)===
	* Differentiation by level of decomposition for luminance and chrominance (fine and coarse).		* Differentiation by level of decomposition for luminance and chrominance (fine and coarse).
	* Pixel differentiation for luminance and possibility of taking hue into account.		* Pixel differentiation for luminance and possibility of taking hue into account.
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	==Denoising with « Local adjustments » ~~and "Non-local means"~~==		==Denoising with « Local adjustments »==

	===Steps in the process===		===Steps in the process===

Jdc at 07:53, 5 February 2021

2021-02-05T07:53:26Z

← Older revision		Revision as of 07:53, 5 February 2021
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	==Improvements with "Non-local means" - also called patch-based denoise (Local Adjustments tab) february 2021==		==Improvements with "Non-local means" - also called patch-based denoise (Local Adjustments tab) february 2021==
	* this algorithm (origin Ipol 2014) was ported to ART by Alberto Griggio and improved by Ingo Weirich, Jacques Desmis adapted it to Rawtherapee.		* this algorithm (origin Ipol 2014 [https://pdfs.semanticscholar.org/a262/269fa4b44b64d750c72fad3887f9d88817ce.pdf]) was ported to ART by Alberto Griggio and improved by Ingo Weirich, Jacques Desmis adapted it to Rawtherapee.
	~~[https://pdfs.semanticscholar.org/a262/269fa4b44b64d750c72fad3887f9d88817ce.pdf]~~
	* What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.		* What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.

Jdc at 07:51, 5 February 2021

2021-02-05T07:51:41Z

← Older revision		Revision as of 07:51, 5 February 2021
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	==Improvements with "Non-local means" - also called patch-based denoise (Local Adjustments tab) february 2021==		==Improvements with "Non-local means" - also called patch-based denoise (Local Adjustments tab) february 2021==
	* this algorithm (origin Ipol 2014) was ported to ART by Alberto Griggio and improved by Ingo Weirich, Jacques Desmis adapted it to Rawtherapee.		* this algorithm (origin Ipol 2014) was ported to ART by Alberto Griggio and improved by Ingo Weirich, Jacques Desmis adapted it to Rawtherapee.
			[https://pdfs.semanticscholar.org/a262/269fa4b44b64d750c72fad3887f9d88817ce.pdf]
	* What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.		* What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.

Jdc at 07:10, 5 February 2021

2021-02-05T07:10:37Z

← Older revision		Revision as of 07:10, 5 February 2021
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	* Ability to use Lab* mode instead of RGB mode.		* Ability to use Lab* mode instead of RGB mode.
	* Addition of median filter denoising		* Addition of median filter denoising

			==Improvements with "Non-local means" - also called patch-based denoise (Local Adjustments tab) february 2021==
			* this algorithm (origin Ipol 2014) was ported to ART by Alberto Griggio and improved by Ingo Weirich, Jacques Desmis adapted it to Rawtherapee.
			* What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.

	==A few remarks==		==A few remarks==
	Denoising is subject to a lot of debate, often controversial. There is also a lot of dogma and quarrels surrounding the methods and tools. My position on the following subjects is to be pragmatic. What counts is the final result.		Denoising is subject to a lot of debate, often controversial. There is also a lot of dogma and quarrels surrounding the methods and tools. My position on the following subjects is to be pragmatic. What counts is the final result.


	==Where should the denoise functions be located?==		==Where should the denoise functions be located?==
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	* Use of an Excluding Spot to recover noisy areas.		* Use of an Excluding Spot to recover noisy areas.
	* No tiling: this means that when you work in full-image mode and the image is > ~30Mb, you will need more than 8Gb of RAM to work without crashing.		* No tiling: this means that when you work in full-image mode and the image is > ~30Mb, you will need more than 8Gb of RAM to work without crashing.
	* Since february 2021 - Non-local means (Patch-based denoise):		* Since february 2021 - Non-local means (Patch-based denoise).
	** What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.
	==Which modules should you use?==		==Which modules should you use?==
	It is very difficult to answer this question, unless you want to denoise just part of the image. In this case you need to use Blur/Grain & Denoise in the Local Adjustments tab.		It is very difficult to answer this question, unless you want to denoise just part of the image. In this case you need to use Blur/Grain & Denoise in the Local Adjustments tab.

← Older revision		Revision as of 05:27, 13 June 2021
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	* Using automatic tiling for both wavelet and DCT operations to reduce memory requirements.		* Using automatic tiling for both wavelet and DCT operations to reduce memory requirements.

	Note that in the beginning, the ~~"Denoise"~~ module was at the end of the process (this was also the case for the PerfectRAW product which I worked on with E.Martinec and M.LLorens).		Note that in the beginning, the Noise Reduction module was at the end of the process (this was also the case for the PerfectRAW product which I worked on with E.Martinec and M.LLorens).

	==Enhancements to original features carried out between 2012 & 2020==		==Enhancements to original features carried out between 2012 & 2020==
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	==Improvements with "Non-local means" - also called patch-based denoise (Local Adjustments tab) February 2021.==		==Improvements with "Non-local means" - also called patch-based denoise (Local Adjustments tab) February 2021.==

	* ~~this~~ algorithm (origin Ipol 2014 [https://pdfs.semanticscholar.org/a262/269fa4b44b64d750c72fad3887f9d88817ce.pdf]) was ported to ART by Alberto Griggio and improved by Ingo Weyrich, Jacques Desmis adapted it to RawTherapee.		* This algorithm (origin Ipol 2014 [https://pdfs.semanticscholar.org/a262/269fa4b44b64d750c72fad3887f9d88817ce.pdf]) was ported to ART by Alberto Griggio and improved by Ingo Weyrich, Jacques Desmis adapted it to RawTherapee.

	* What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.		* What is patch-based denoise? Contrary to the usual filters that reduce noise by averaging the values of groups of pixels located around a target pixel, non-local means filters average the values of all the pixels in the image and weight them according to their similarity with the target pixel. This type of filtering reduces the loss of detail compared to filters that use local averaging.
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	It is very difficult to answer this question, unless you want to denoise just part of the image. In this case you need to use Blur/Grain & Denoise in the Local Adjustments tab.		It is very difficult to answer this question, unless you want to denoise just part of the image. In this case you need to use Blur/Grain & Denoise in the Local Adjustments tab.
	Nevertheles :		Nevertheles :
	* ~~with~~ noisy or very noisy raw images from older cameras with smaller sensors, the Noise Reduction module in the Detail tab is essential and easy to use.		* With noisy or very noisy raw images from older cameras with smaller sensors, the Noise Reduction module in the Detail tab is essential and easy to use.
	* ~~with~~ recent low-noise raw files, the Blur/Grain & Denoise module in the Local Adjustments tab is by far the most comprehensive even if it is a little complex.		* With recent low-noise raw files, the Blur/Grain & Denoise module in the Local Adjustments tab is by far the most comprehensive even if it is a little complex.
	* The Denoise & Refine module in Wavelet Levels (Advanced tab) has the advantage of being part of the same interface as the other wavelet-processing tools thereby making it easier to tweak the settings in conjunction with the other wavelet parameters.		* The Denoise & Refine module in Wavelet Levels (Advanced tab) has the advantage of being part of the same interface as the other wavelet-processing tools thereby making it easier to tweak the settings in conjunction with the other wavelet parameters.
	* ~~there~~ is no point in using all 3 together. However, for noisy images the combination of Noise Reduction and one of the other modules either in Wavelet Levels or Local Adjustments is recommended.		* There is no point in using all 3 together. However, for noisy images the combination of Noise Reduction and one of the other modules either in Wavelet Levels or Local Adjustments is recommended.

	==Denoising with Local adjustments==		==Denoising with Local adjustments==
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	====Luma detail recovery (DCT f - uses Fourier transform and wavelets)====		====Luma detail recovery (DCT f - uses Fourier transform and wavelets)====

	This slider uses a Fourier transform to take into account the difference between the L (Lab*) component of the wavelet-denoised image and the original image. It is important not to set this slider to zero because in this case, the Fourier transform will have a ~~overlay~~ strong effect on the noise and prevent the 3 equalizers from having any real influence. The more the slider is moved to the right, the weaker the DCT action will be and the more the details will be apparent.		This slider uses a Fourier transform to take into account the difference between the L (Lab*) component of the wavelet-denoised image and the original image. It is important not to set this slider to zero because in this case, the Fourier transform will have a overly strong effect on the noise and prevent the 3 equalizers from having any real influence. The more the slider is moved to the right, the weaker the DCT action will be and the more the details will be apparent.

	====Equalizer white-black (uses data prior to wavelet processing)====		====Equalizer white-black (uses data prior to wavelet processing)====
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	====Denoise based on luminance mask (uses data prior to wavelet processing)====		====Denoise based on luminance mask (uses data prior to wavelet processing)====

	* The mask in Mask and modifications (Blur & ~~denoise~~ ) must be activated.		* The mask in Mask and modifications (Blur & Denoise ) must be activated.
	* One or both of the two curves L(L) - LC(H) must be activated.		* One or both of the two curves L(L) - LC(H) must be activated.
	* The slider "Dark area luma threshold" allows you to choose the luminance level. below which the action of the "Luminance denoise by level" curve will be reinforced.		* The slider "Dark area luma threshold" allows you to choose the luminance level. below which the action of the "Luminance denoise by level" curve will be reinforced.
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	===="Edge detection - DCT" > Luma and chroma detail threshold (DCT f - uses Fourier transforms and wavelets)====		===="Edge detection - DCT" > Luma and chroma detail threshold (DCT f - uses Fourier transforms and wavelets)====

	This slider tries to take into account the edge effect of the original image in order to differentiate the action between uniform areas and areas with detail. Two algorithms are available (both from ART.)		This slider tries to take into account the edge effect of the original image in order to differentiate the action between uniform areas and areas with detail. Two algorithms are available (both from ART)
	* "buildblendmask" - similar function to that used to differentiate demosaicing, for example.		* "buildblendmask" - similar function to that used to differentiate demosaicing, for example.
	* "Laplacian"		* "Laplacian"
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	====Non-local means - patch-based denoise====		====Non-local means - patch-based denoise====

	Can be used in conjunction with Wavelets and DCT or alone. It allows a very efficient luminance noise reduction. It will notably differentiate between flatness and texture.		Can be used in conjunction with Wavelets and DCT or alone. It allows very efficient luminance noise reduction. It will notably differentiate between flatness and texture.

	====Fine chroma (uses wavelets)====		====Fine chroma (uses wavelets)====
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	====Chroma detail recovery (DCT – uses Fourier transforms and wavelets)====		====Chroma detail recovery (DCT – uses Fourier transforms and wavelets)====

	This slider uses ~~the~~ Fourier transform to take into account the difference between the "a" and "b" (Lab*) components of the wavelet-denoised image and the original image. It is important not to set this slider to zero because the Fourier transform will have a overly strong effect on the noise and prevent the edge detection from having any real influence. The more the slider is moved to the right, the weaker the DCT action will be and the more the color details will be apparent.		This slider uses a Fourier transform to take into account the difference between the "a" and "b" (Lab*) components of the wavelet-denoised image and the original image. It is important not to set this slider to zero because the Fourier transform will have an overly strong effect on the noise and prevent the edge detection from having any real influence. The more the slider is moved to the right, the weaker the DCT action will be and the more the color details will be apparent.

	====Recovery based on luminance mask (uses data before and after denoise processing)====		====Recovery based on luminance mask (uses data before and after denoise processing)====
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	This module acts on the difference between the original noisy image and the denoised image processed with the above tools. Completely black areas in the mask will retain the denoise settings whereas completely white areas will retain the image settings prior to denoising.		This module acts on the difference between the original noisy image and the denoised image processed with the above tools. Completely black areas in the mask will retain the denoise settings whereas completely white areas will retain the image settings prior to denoising.

	* The mask in Mask and modifications (Blur & ~~denoise~~ ) must be activated.		* The mask in Mask and modifications (Blur & Denoise ) must be activated.
	* One or both of the two curves L(L) - LC(H) must be activated.		* One or both of the two curves L(L) - LC(H) must be activated.
	* The "Dark area luma threshold" slider allows you to choose the luminance level below which the denoise settings will be progressively applied.		* The "Dark area luma threshold" slider allows you to choose the luminance level below which the denoise settings will be progressively applied.
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	* Between the two values, the image will be preserved without denoising, unless the "Gray area luma denoise" slider is greater than 0; this can be useful for example to attenuate any unsightly chromatic noise.		* Between the two values, the image will be preserved without denoising, unless the "Gray area luma denoise" slider is greater than 0; this can be useful for example to attenuate any unsightly chromatic noise.
	* The "Recovery threshold" slider allows you to choose the level of denoise that will be applied below or above the "dark" and "light" thresholds respectively.		* The "Recovery threshold" slider allows you to choose the level of denoise that will be applied below or above the "dark" and "light" thresholds respectively.
	* The Decay strentgh slider allows you to choose the rate at which the attenuation or amplification will be progressively applied.		* The "Decay strentgh" slider allows you to choose the rate at which the attenuation or amplification will be progressively applied.

	===Note on masks===		===Note on masks===

	* You can use a lockable Color Picker (LCP) to help identify the extent to which the different parts of the mask will attenuate or maintain the denoise settings. To ensure that the LCP information corresponds to the slider values, the “Background color/~~luma”~~ must be set to zero in Settings.		* You can use a lockable Color Picker (LCP) to help identify the extent to which the different parts of the mask will attenuate or maintain the denoise settings. To ensure that the LCP information corresponds to the slider values, the “Background color/luma mask” must be set to zero in Settings.
	* You can use the Mask Tools (see below) in association with the LCP, to adjust the gray areas and make them lighter or darker, thereby adjusting the amount of denoise that is applied.		* You can use the Mask Tools (see below) in association with the LCP, to adjust the gray areas and make them lighter or darker, thereby adjusting the amount of denoise that is applied.
	Mask Tools: "Structure mask", "Smooth radius", "Gamma", "Slope", "Shadows", "Curve L(L)", "Local contrast(L)" curve, curve using wavelets.		Mask Tools: "Structure mask", "Smooth radius", "Gamma", "Slope", "Shadows", "Curve L(L)", "Local contrast(L)" curve, curve using wavelets.