Version: 2.0.0 (using KDE 4.6.2) OS: Linux Hello, When searching through lots of pictures (15.000, e.g.), it would be very advantegous if there was a way to mark unsharp pics in the collection. In editing modus, lens correction there is already a procedure to affect sharpness. Thats why I am hoping there is an algorithm to detect sharpness of a pic. Going through huge numbers of pics, it would help to mark pics automatically, may in classes: class I: perfectly sharp class II: satisfying sharpness most areas of the pic class III: misty pics, with no sharp area borders. I guess, one could deal with sharpness detection by analysing some small areas (diameter or square of 20 picels wide, e.g.). For the sake of analysing speed, there could be a statistical approach to determine this information only on (statistically) selected areas. This would easy getting better workflow, I assume, as manual and time-consuming work could be concentrated on worthy pics. Maybe it is not necessary for all users, and not for all times; but maybe a switch could enable this feature. Axel Axel Reproducible: Always Steps to Reproduce: not avaliable Actual Results: not avaliable Expected Results: should be implemented OS: Linux (i686) release 2.6.35-30-generic-pae Compiler: cc
Yep, that would be great...
Created attachment 78517 [details] Algorithm: Finding blurry images Basic algorithm which returns a low value when image is blurry and vice versa. Requires openCV. Needs one image input. To build it, cmake . and make it. Please give feedback.
Dear Gowtham: Wonderful to read, that you are working on this issue! Unfortunately, I am not a programmer or software-specialist. So, I will try to describe my primary intentions with reflection to some approaches available. In modern DLRs they use several ways to get to sharpness- you may want to check http://en.wikipedia.org/wiki/Autofocus . If this would resonable to copy one of these methods: I do not know. Maybe the preconditions are different: in reality, when taking a picture, we have a reduction from 3D to 2d. When searching unsharp pictures within a collection, we have "pure 2D". As a matter of fact, when I suggestet this issue, I had in my mind: checking large picture collection automatically for _completely_ unsharp pic to have some type of automated filter-function. So, my intention was originally, to have some sorting-function. This would be a much weaker demand than we have in autofocus in modern DLRs. Isn't it? Ok, when "sorting out", there should be a remaining lot of pics which do _not_ fulfil this sharpness criterium. These pics has to be marked out to check these manually. As an artists intentions maybe changing and lead by art, not mathematical rules. For my opinion, the original pic has the highest value. Yours, Axel Am 31.03.2013 01:01, schrieb Gowtham Ashok: > https://bugs.kde.org/show_bug.cgi?id=279544 > > --- Comment #2 from Gowtham Ashok <gwty93@gmail.com> --- > Created attachment 78517 [details] > --> https://bugs.kde.org/attachment.cgi?id=78517&action=edit > Algorithm: Finding blurry images > > Basic algorithm which returns a low value when image is blurry and vice versa. > Requires openCV. Needs one image input. > To build it, cmake . and make it. > Please give feedback. >
I have used a concept similar to autofocus in the code. Better Explanation: http://www.howstuffworks.com/autofocus3.htm Yes, after image is taken, we do not have any data about the distance of the camera from the subject(that is why we have to use passive autofocus). Sharp or blurry is somewhat subjective. There are also cases where the photographer intended to give a blur effect, or while taking a shot of a fast-moving object. http://img.ehowcdn.com/article-new/ehow/images/a05/ah/vv/fast-f1-car_-800x800.jpg So, if we can take care of this, we can probably have a useful image classification algorithm. We can also combine this with face detection algorithm to give better output.
I can tell you just- some considerations. Thank you for the links, content, I read with great interest. "sharp or blurry .. subjective": you are right, and, maybe even more difficult, it might be intentional in certain cases. I agree. The smple for fast moving object is another topic, which comes instanteneously in my mind: but in contradiction to that, there should be a possiblitzy to "filter" any linear or even non-linear movement. And derive a sharp pic inversely, when substraction the dislocation vector. I am happy that you seem to be able to take care of this issue. For my opinion, this inverse procedure could be an intelligent way to sharpen even blurry pics- under the precondition, that there is a (mathematical) linear movement involved. mathematoical linear. I mean, a movement path which coul be a strauigtgt line, a periodic ("wavy") function or something similar. !! I guess, we should distinguish between filterung blurry pics ("BPF") and gaining sharp pics from ones the the blurry because of moving te lens while exposing a pic. !! Am 31.03.2013 11:44, schrieb Gowtham Ashok: > https://bugs.kde.org/show_bug.cgi?id=279544 > > Gowtham Ashok <gwty93@gmail.com> changed: > > What |Removed |Added > ---------------------------------------------------------------------------- > CC| |gwty93@gmail.com > > --- Comment #4 from Gowtham Ashok <gwty93@gmail.com> --- > I have used a concept similar to autofocus in the code. > Better Explanation: > http://www.howstuffworks.com/autofocus3.htm > > Yes, after image is taken, we do not have any data about the distance of the > camera from the subject(that is why we have to use passive autofocus). > > Sharp or blurry is somewhat subjective. There are also cases where the > photographer intended to give a blur effect, or while taking a shot of a > fast-moving object. > http://img.ehowcdn.com/article-new/ehow/images/a05/ah/vv/fast-f1-car_-800x800.jpg > > So, if we can take care of this, we can probably have a useful image > classification algorithm. > We can also combine this with face detection algorithm to give better output. >
Dear Gotham: Maybe you still work on this issue? As I found several hits in this context recently, I assume, finding sharp/unsharp pics automatically could be a technologgy of the future. Recent article in a leading German computer paper: http://www.heise.de/ct/inhalt/2013/18/68/ "Verwackelkandidate" (meaning "de-unsharp-utitility") Others. - http://www.heise.de/download/image-analyzer-1121815.html - http://logicnet.dk/Analyzer/ I guess, you'll keepo track with relevant developments? All the best Axel Am 31.03.2013 13:44, schrieb Gowtham Ashok: > https://bugs.kde.org/show_bug.cgi?id=279544 > > Gowtham Ashok <gwty93@gmail.com> changed: > > What |Removed |Added > ---------------------------------------------------------------------------- > CC| |gwty93@gmail.com > > --- Comment #4 from Gowtham Ashok <gwty93@gmail.com> --- > I have used a concept similar to autofocus in the code. > Better Explanation: > http://www.howstuffworks.com/autofocus3.htm > > Yes, after image is taken, we do not have any data about the distance of the > camera from the subject(that is why we have to use passive autofocus). > > Sharp or blurry is somewhat subjective. There are also cases where the > photographer intended to give a blur effect, or while taking a shot of a > fast-moving object. > http://img.ehowcdn.com/article-new/ehow/images/a05/ah/vv/fast-f1-car_-800x800.jpg > > So, if we can take care of this, we can probably have a useful image > classification algorithm. > We can also combine this with face detection algorithm to give better output. >
Hello Axel, Thanks for the links. Gilles, Marcel and me are working on adding this feature to digiKam. For more information, please refer to http://www.google-melange.com/gsoc/proposal/review/google/gsoc2013/gwty/1
Dear Gotham, Gilles and Marcel, This sounds absolutely great! I believe this project has a good chance to force through against commercial prgs. Thank you for your efforts! Axel -- Am 24.08.2013 13:44, schrieb Gowtham Ashok: > https://bugs.kde.org/show_bug.cgi?id=279544 > > --- Comment #7 from Gowtham Ashok <gwty93@gmail.com> --- > Hello Axel, > > Thanks for the links. Gilles, Marcel and me are working on adding this feature > to digiKam. > > For more information, please refer to > http://www.google-melange.com/gsoc/proposal/review/google/gsoc2013/gwty/1 >
Am 24.08.2013 13:44, schrieb Gowtham Ashok: > https://bugs.kde.org/show_bug.cgi?id=279544 > > --- Comment #7 from Gowtham Ashok <gwty93@gmail.com> --- > Hello Axel, > > Thanks for the links. Gilles, Marcel and me are working on adding this feature > to digiKam. > > For more information, please refer to > http://www.google-melange.com/gsoc/proposal/review/google/gsoc2013/gwty/1 > Dear Gowtham: My original intention reffered on blur- which comes more and more objective. NIKON advices certain techniques to reduce bluring effects see <http://www.nikonusa.com/en_US/o/Y6wrkA9OU_z04IreazIXl_22UII/PDF/D800_TechnicalGuide_En.pdf> for its Model D800 / D800 E. (I own one- great machine, 36 MPixels ;-)! ) From my fotographical practise, I experienced, that blur can be an interesting effect. But, most of the time, we want or even need to avoid this unsharpness type! When having _real_ fotographic situations in mind, I feel, that _linear_ transitions ("mistakes, unsharpness effects") are _not_ the single interesting ones. There can be circular or bow-shaped transitions or others. Imagine, a photographer stands in the wind and get hit by a gust of wind. Not having a tripod because of weight limitations. The movement of an imaginary pics point will then _not_ follow a line nor a circle but rather more a _freely_ curved line. --- Another type of mistake maybe related to the artefacts/mistakes, you mentioned in your descriptive http://www.google-melange.com/gsoc/proposal/review/google/gsoc2013/gwty/1 What happens, if some parts of a pic are too bright by far? Maybe there is a way to reconstruct the brightness distribution around such a brigthish area using neural network approaches for self learning procedures, how "burned-out" areas can be filled according to surronding areas? And still keep similar appearences compared to the surrounding areas? -- I mention this idea to show, that I guess, the borderline between filtering for quality and impoving is not a fixed line at all but needs interpretation. Maybe numerical interpretation? Besides, some number characteristics could help to concentrate on such pics which are worth for improving techniques or- not. Some further thoughts- Yours Axel
Implemented in 4.0.0 release. Gilles Caulier