Abstract—In this paper we examine the problem of bit allocation in lossy image set compression. Instead of treating each image independently, image set compression algorithms examine the relationships among similar images and remove inter-image redundancies to improve compression performance. These algorithms map the original image set into a number of prediction residual images to be coded. Typically the same bit rate is used to encode each residual. We show that a rate-distortion approach based on Lagrangian optimization can lead to further improvement in image set compression algorithms. Index Terms—Image set compression, bit allocation. I
Image set compression has recently emerged as an active research topic due to the rapidly increasing...
Many research works have been developed for stereo image com-pression purpose where most of them aim...
Image set coding improves the compression efficiency by reducing both intra-and inter-image redundan...
In this paper we provide an overview of rate-distortion (R-D) based optimization techniques and thei...
Lossy plus lossless techniques for image compression split an image into a low-bit-rate lossy repres...
One of the main part of image compression is a quantization process which give a significant effect ...
Image compression leads to minimize the storage-requirement of an image by reducing the size of the ...
Abstract—An automatic compression strategy proposed by Gergel et al. is a near-optimal lossy compres...
We present a framework for optimal rate allocation to image subbands to minimize the distortion in t...
In this paper, analytical modelling of the operational R-D characteristics that can significantly re...
A bit rate allocation (BRA) strategy is needed to optimally compress three-dimensional (3-D) data on...
In this paper, we propose a novel image set compression approach based on sparse coding with an orde...
We show that the complete information that is available after an image has been encoded is not just ...
The biggest challenge in image set compression is how to efficiently remove the set redundancy among...
We present a new Lagrangian-based iterative technique for rate--distortion optimization under multip...
Image set compression has recently emerged as an active research topic due to the rapidly increasing...
Many research works have been developed for stereo image com-pression purpose where most of them aim...
Image set coding improves the compression efficiency by reducing both intra-and inter-image redundan...
In this paper we provide an overview of rate-distortion (R-D) based optimization techniques and thei...
Lossy plus lossless techniques for image compression split an image into a low-bit-rate lossy repres...
One of the main part of image compression is a quantization process which give a significant effect ...
Image compression leads to minimize the storage-requirement of an image by reducing the size of the ...
Abstract—An automatic compression strategy proposed by Gergel et al. is a near-optimal lossy compres...
We present a framework for optimal rate allocation to image subbands to minimize the distortion in t...
In this paper, analytical modelling of the operational R-D characteristics that can significantly re...
A bit rate allocation (BRA) strategy is needed to optimally compress three-dimensional (3-D) data on...
In this paper, we propose a novel image set compression approach based on sparse coding with an orde...
We show that the complete information that is available after an image has been encoded is not just ...
The biggest challenge in image set compression is how to efficiently remove the set redundancy among...
We present a new Lagrangian-based iterative technique for rate--distortion optimization under multip...
Image set compression has recently emerged as an active research topic due to the rapidly increasing...
Many research works have been developed for stereo image com-pression purpose where most of them aim...
Image set coding improves the compression efficiency by reducing both intra-and inter-image redundan...