But even if it's not possible to avoid keeping frames kind of seperate with regards to their temporal placement - wouldn't it still be possible and even beneficial to overcome the "one (I-)frame is the golden reference taking much more bits to encode than every other in a GOP"-paradigma?
I would assume that even if you choose which frame to encode as an I-frame cleverly, chances are that this I-frame will contain parts (e.g. out-of-focus or motion-blurred areas) that could have been derived from another frame in the GOP (where the same objects are more in focus or less motion blurred) better while spending bits more efficiently there.
I could envision that all frames of a GOP are first scanned for regions that are (a) rich of detail information and (b) have less detail-rich counterparts in other frames of a GOP, and then any frame of a GOP could be declared "the reference frame for a certain region", which the other frames only encode differences to.
BTW: Has "blurring" of a region, in general, ever been considered to be a useful transformation that helps encoding part of a frame from another frame that holds a "sharper" version of the same region? I would expect that one could often find both "blurred" and "sharp" versions of the same objects within a sequence of frames, do to motion of that object starting or stopping.
While I am in brainstorming mode, one more completely different, wild idea: You've certainly heard of seam-carving and the C/C++ library "Liquid Rescale" that implements it. I wonder whether anybody has ever considered using seam carving for compression purposes. I am not quite sure this would work, but theoretically, one could try to re-target an image to a smaller size during compression (finally compressing the residual smaller image) and do the reverse during decompression. That, of course, would lose information, and maybe it's of no practical use. But unless falsified, one could speculate that a an image retargeted to really small dimensions might be usable as an interesting "prediction" start point for reconstructing the full-size image, because seam carving has the tendency to get rid of image areas that aren't so important to human viewers, anyway.
Hope you don't get bored reading my ideas, but I had to spill them somewhere :-)
Re: What about thinking outside the box of I-/B-/P-Frames?
Date: 2014-12-26 12:01 am (UTC)But even if it's not possible to avoid keeping frames kind of seperate with regards to their temporal placement - wouldn't it still be possible and even beneficial to overcome the "one (I-)frame is the golden reference taking much more bits to encode than every other in a GOP"-paradigma?
I would assume that even if you choose which frame to encode as an I-frame cleverly, chances are that this I-frame will contain parts (e.g. out-of-focus or motion-blurred areas) that could have been derived from another frame in the GOP (where the same objects are more in focus or less motion blurred) better while spending bits more efficiently there.
I could envision that all frames of a GOP are first scanned for regions that are (a) rich of detail information and (b) have less detail-rich counterparts in other frames of a GOP, and then any frame of a GOP could be declared "the reference frame for a certain region", which the other frames only encode differences to.
BTW: Has "blurring" of a region, in general, ever been considered to be a useful transformation that helps encoding part of a frame from another frame that holds a "sharper" version of the same region? I would expect that one could often find both "blurred" and "sharp" versions of the same objects within a sequence of frames, do to motion of that object starting or stopping.
While I am in brainstorming mode, one more completely different, wild idea: You've certainly heard of seam-carving and the C/C++ library "Liquid Rescale" that implements it. I wonder whether anybody has ever considered using seam carving for compression purposes. I am not quite sure this would work, but theoretically, one could try to re-target an image to a smaller size during compression (finally compressing the residual smaller image) and do the reverse during decompression. That, of course, would lose information, and maybe it's of no practical use. But unless falsified, one could speculate that a an image retargeted to really small dimensions might be usable as an interesting "prediction" start point for reconstructing the full-size image, because seam carving has the tendency to get rid of image areas that aren't so important to human viewers, anyway.
Hope you don't get bored reading my ideas, but I had to spill them somewhere :-)