Are you thinking of having denoiser as an extra binary like for Renderman ? So it could be use with other renderer and/or outside of blender as well ?
2016-03-22 15:46 GMT+01:00 Fabrizio Destro <[email protected]>: > Thank you for your feedback. I am going to read them. > I am currently working on my proposal, all suggestions are welcome > > > https://docs.google.com/document/d/18UkmWPSoMutiJaxr5mXDkkB4ccyqu0nC19xVb2qdq-0/edit?usp=sharing > > > On Tue, Mar 22, 2016 at 11:16 AM, Sergey Sharybin <[email protected]> > wrote: > > > > Hi, > > > > General idea of denoisers is to blur noisy areas. Now, how to detect if > the > > area is noisy or not? There are several approaches to this: it could be > > image-space variance based approach or it could be an approach based on > > per-pixel variance. The later one seemed to be more promising from own > > experiments. Additionally, you should not blur background with foreground > > (roughly speaking) and you'll need to have a way to distinguish areas > which > > could be blurred together and which are not. It could be based on depth, > > normal, UV coordinate and so on. All this extra information requires > extra > > memory.. That's what wiki meant basically. > > > > I think we'll indeed need to have some sort of "framework" for denoising, > > so we'll be able to have quick viewport previews with more aggressive > > algorithms (which are usually not so much temporary stable and will cause > > low frequency noise in the animation) and we'll be able to have a less > > aggressive denoiser to simply get rid of last bit of MC noise. > > > > Can't speak of exact milestones, that's something dependent on your exact > > proposal, skills and such.. > > > > You might want to have a look into following papers: > > > > - Filtering and Blending of High-Variance Light Paths with Perceptual > > Control, Karsten Schwenk > > - Guided image filtering, Kaiming He et al. > > - Recent Advantages in Adaptive Sampling and Reconstruction for Monte > Carlo > > Rendering, M. Zwicker et al. > > - Removing the noise in Monte Carlo Rendering with General Image > Denoising > > Algorithms, Nima Khademi Kalantari and Pradeep Sen > > > > (should be easy to find links, i only have those papers printed, no links > > handy) > > > > There were also some interesting presentation at the SIGGRAPH 2015, you > can > > find some notes and papers titles there: > > > http://s2015.siggraph.org/attendees/courses/events/denoising-your-monte-carlo-renders-recent-advances-image-space-adaptive > > > > > > On Mon, Mar 21, 2016 at 11:40 AM, Fabrizio Destro < > [email protected] > > > wrote: > > > > > Hi, thank you for the materials. > > > > > > I've just read "Path-space motion estimation [...]" and for what I've > > > understood they use different tools to reduce the noise on the image: > > > Decompositions, Motion estimations of reflections and other effects, > > > Denoising, Spatial and Temporal upsampling. The first milestone could > > > be to think about a generic framework for denoising in terms of > > > interfaces and modules, and start implementing a 'skeleton'. > > > > > > In their work they cited this research "On Filtering the Noise from > > > the Random Parameters in Monte Carlo Rendering", on this paper they > > > talk about a method to reduce the noise which works in image space. > > > Maybe in a possible schedule the second milestone could be an > > > implementation of denoiser like that, which works only on the image. > > > > > > After these two milestone have been delivered, the next step on the > > > schedule will be the implementation of the modules inside this > > > framework (Motions estimations of relfections, etc...) > > > > > > > > > On Sun, Mar 20, 2016 at 8:10 PM, François T. < > [email protected]> > > > wrote: > > > > Hello, > > > > > > > > Disney has several recent research on the subject... > > > > > > > > https://www.disneyresearch.com/publication/pathspace-decomposition/ > > > > > > > > > > > > https://www.researchgate.net/publication/281678889_Boosting_Histogram-Based_Denoising_Methods_with_GPU_Optimizations > > > > > > > > > > > > > > > > 2016-03-20 19:24 GMT+01:00 Fabrizio Destro < > [email protected]>: > > > > > > > >> Hello everybody! I am Fabrizio I always wanted to contribute to an > > > >> Open Source project. I found out about GSoC about three years ago, > but > > > >> I have never applied because I wouldn't have had the time. But, this > > > >> year I would like to try. > > > >> > > > >> I have looked through the proposed ideas and some of them catch my > > > >> attention. In particularly the Cycles denoiser, I have some > questions > > > >> about it. > > > >> > > > >> First, I want to be sure I understand what the goal is. So, the > > > >> objective is to create a node which, once the rendering is done, > will > > > >> work only on the image with the goal to reduce the noise. > > > >> > > > >> I am not sure about this sentence I found on the wiki: "[...] and > > > >> requires a special buffer with 'delta' information for speed, UV > > > >> [...]". This means that this node will store some data to speed up > the > > > >> process on the next rendering? and if so, these data will be valid > > > >> only if the scene didn't change from the last time, right? > > > >> > > > >> I am currently doing some research online and I found this > publication > > > >> on the subject http://dl.acm.org/citation.cfm?doid=2776880.2792740 > . > > > >> Does someone have any reference which can be useful? or maybe an > idea > > > >> on some algorithms/researches? > > > >> _______________________________________________ > > > >> Bf-committers mailing list > > > >> [email protected] > > > >> http://lists.blender.org/mailman/listinfo/bf-committers > > > >> > > > > > > > > > > > > > > > > -- > > > > ____________________ > > > > François Tarlier > > > > www.francois-tarlier.com > > > > www.linkedin.com/in/francoistarlier > > > > _______________________________________________ > > > > Bf-committers mailing list > > > > [email protected] > > > > http://lists.blender.org/mailman/listinfo/bf-committers > > > _______________________________________________ > > > Bf-committers mailing list > > > [email protected] > > > http://lists.blender.org/mailman/listinfo/bf-committers > > > > > > > > > > > -- > > With best regards, Sergey Sharybin > > _______________________________________________ > > Bf-committers mailing list > > [email protected] > > http://lists.blender.org/mailman/listinfo/bf-committers > _______________________________________________ > Bf-committers mailing list > [email protected] > http://lists.blender.org/mailman/listinfo/bf-committers > -- ____________________ François Tarlier www.francois-tarlier.com www.linkedin.com/in/francoistarlier _______________________________________________ Bf-committers mailing list [email protected] http://lists.blender.org/mailman/listinfo/bf-committers
