Techniques for video exchange are disclosed in which a video source sends redundant copies of video coded at a given presentation time. A decoder may determine, from metadata stored with a first decoded frame, whether other decoded frames have been designated as correlated to the first decoded frame. If so, the decoder may fetch other decoding frames using time indicator values of other decoded frames in metadata stored with the first decoded frame. When other decoded frame(s) are found, the decoder may blend content of the first coded frame and the other decoded frame(s). The decoder may render the blended frame. When one such coded frame is an intra-coded frame, the proposed technique may alleviate beating artifacts by blending recovered data of the intra-coded frame with recovered data of another frame, which may be inter-coded.

Disclosed are techniques for dynamic compression of audio-visual data, including a method for reducing a size of media content, comprising identifying a scene to be captured by a capture device, wherein the scene comprises a plurality of objects, and determining whether at least one of: (i) an available storage in the capture device to store a digital media file associated with the scene; and (ii) an available network bandwidth to transfer the digital media file is below an associated threshold. In response to the threshold determination, some embodiments may further comprise analyzing the plurality of objects to determine which objects can be redeveloped by a GAN regeneration module to a threshold quality level and which objects cannot be redeveloped with the GAN regeneration module to the threshold quality level, generating an optimized capture plan based on the analyzing, and encoding the scene pursuant to the optimized capture plan.

Disclosed are techniques for dynamic compression of audio-visual data, including a method for reducing a size of media content, comprising identifying a scene to be captured by a capture device, wherein the scene comprises a plurality of objects, and determining whether at least one of: (i) an available storage in the capture device to store a digital media file associated with the scene; and (ii) an available network bandwidth to transfer the digital media file is below an associated threshold. In response to the threshold determination, some embodiments may further comprise analyzing the plurality of objects to determine which objects can be redeveloped by a GAN regeneration module to a threshold quality level and which objects cannot be redeveloped with the GAN regeneration module to the threshold quality level, generating an optimized capture plan based on the analyzing, and encoding the scene pursuant to the optimized capture plan.

A scene-based image processing method includes: performing decoding after acquiring video data to obtain multiple image frames, and identifying key frame images by performing key frame detection (S10); analyzing similarity between the content of two adjacent key frame images, and determining whether the difference in the content of the two adjacent key frame images is within a preset threshold (S20); and when the difference in the content of the two adjacent key frame images is within the preset threshold, determining that the two adjacent key frame images are a same scene, uniformly performing image feature statistics compilation, overlaying feature information, and performing image enhancement on a same scene by using a similar enhancement processing curve (S30).

A scene-based image processing method includes: performing decoding after acquiring video data to obtain multiple image frames, and identifying key frame images by performing key frame detection (S10); analyzing similarity between the content of two adjacent key frame images, and determining whether the difference in the content of the two adjacent key frame images is within a preset threshold (S20); and when the difference in the content of the two adjacent key frame images is within the preset threshold, determining that the two adjacent key frame images are a same scene, uniformly performing image feature statistics compilation, overlaying feature information, and performing image enhancement on a same scene by using a similar enhancement processing curve (S30).

In a method to improve backwards compatibility when decoding high-dynamic range images coded in a wide color gamut (WCG) space which may not be compatible with legacy color spaces, hue and/or saturation values of images in an image database are computed for both a legacy color space (say, YCbCr-gamma) and a preferred WCG color space (say, IPT-PQ). Based on a cost function, a reshaped color space is computed so that the distance between the hue values in the legacy color space and rotated hue values in the preferred color space is minimized HDR images are coded in the reshaped color space. Legacy devices can still decode standard dynamic range images assuming they are coded in the legacy color space, while updated devices can use color reshaping information to decode HDR images in the preferred color space at full dynamic range.

In a method to improve backwards compatibility when decoding high-dynamic range images coded in a wide color gamut (WCG) space which may not be compatible with legacy color spaces, hue and/or saturation values of images in an image database are computed for both a legacy color space (say, YCbCr-gamma) and a preferred WCG color space (say, IPT-PQ). Based on a cost function, a reshaped color space is computed so that the distance between the hue values in the legacy color space and rotated hue values in the preferred color space is minimized HDR images are coded in the reshaped color space. Legacy devices can still decode standard dynamic range images assuming they are coded in the legacy color space, while updated devices can use color reshaping information to decode HDR images in the preferred color space at full dynamic range.

A scene-based image processing method includes: performing decoding after acquiring video data to obtain multiple image frames, and identifying key frame images by performing key frame detection (S10); analyzing similarity between the content of two adjacent key frame images, and determining whether the difference in the content of the two adjacent key frame images is within a preset threshold (S20); and when the difference in the content of the two adjacent key frame images is within the preset threshold, determining that the two adjacent key frame images are a same scene, uniformly performing image feature statistics compilation, overlaying feature information, and performing image enhancement on a same scene by using a similar enhancement processing curve (S30).

A scene-based image processing method includes: performing decoding after acquiring video data to obtain multiple image frames, and identifying key frame images by performing key frame detection (S10); analyzing similarity between the content of two adjacent key frame images, and determining whether the difference in the content of the two adjacent key frame images is within a preset threshold (S20); and when the difference in the content of the two adjacent key frame images is within the preset threshold, determining that the two adjacent key frame images are a same scene, uniformly performing image feature statistics compilation, overlaying feature information, and performing image enhancement on a same scene by using a similar enhancement processing curve (S30).

Disclosed are techniques for dynamic compression of audio-visual data, including a method for reducing a size of media content, comprising identifying a scene to be captured by a capture device, wherein the scene comprises a plurality of objects, and determining whether at least one of: (i) an available storage in the capture device to store a digital media file associated with the scene; and (ii) an available network bandwidth to transfer the digital media file is below an associated threshold. In response to the threshold determination, some embodiments may further comprise analyzing the plurality of objects to determine which objects can be redeveloped by a GAN regeneration module to a threshold quality level and which objects cannot be redeveloped with the GAN regeneration module to the threshold quality level, generating an optimized capture plan based on the analyzing, and encoding the scene pursuant to the optimized capture plan.