Post-compression Rate-distortion Optimization Research Articles

High Throughput JPEG 2000 for Video Content Production and Delivery Over IP Networks

ITU-T Rec T.814 | IS 15444-15, known as High Throughput JPEG 2000, or simply HTJ2K, is Part-15 in the JPEG 2000 series of standards, published in 2019 by the ITU and ISO/IEC. JPEG 2000 Part-1 has long been used as a key component in the production, archival and distribution of video content, as the distribution format for Digital Cinema, and an Interoperable Master Format from which streaming video services are commonly derived. JPEG 2000 has one of the richest feature sets of any coding standard, including scalability, region-of-interest accessibility and non-iterative optimal rate control. HTJ2K addresses a long-standing limitation of the original JPEG 2000 family of standards: relatively low throughput on CPU and GPU platforms. HTJ2K introduces an alternative block coding algorithm that allows extremely high processing throughputs, while preserving all other aspects of the JPEG 2000 framework and offering truly reversible transcoding with the original block coded representation. This paper demonstrates the benefits that HTJ2K brings to video content production and delivery, including cloud-based processing workflows and low latency video content streaming over IP networks, considering CPU, GPU and FPGA-based platforms. For non-iterative optimal rate control, HTJ2K encoders with the highest throughputs and lowest hardware encoding footprints need a strategy for constraining the number of so-called HT-Sets that are generated ahead of the classic Post-Compression Rate-Distortion optimization (PCRD-opt) process. This paper describes such a strategy, known as CPLEX, that involves a second (virtual) rate-control process. The novel combination of this virtual (CPLEX) and actual (PCRD-opt) processes has many benefits, especially for hardware encoders, where memory size and memory bandwidth are key indicators of complexity.

Regional bit allocation with visual attention and distortion sensitivity

This paper proposes a regional rate allocation method for enhancing the perceived quality in image compression. Bit allocation to image regions should be performed by considering the viewer’s attention and distortion sensitivity maps in order to address subjective quality concerns. The paper first proposes an exponential model for the relation between the viewer’s fixation duration and perceived information. The human visual system is more sensitive to the distortion around edges than the distortion in complex textured regions. Therefore, a novel distortion sensitivity method is also proposed that distinguishes true edges from complex textures without using edge detectors or gradient magnitude thresholds. The estimates for the visual attention level and the distortion sensitivity level are jointly used to modify the distortion contribution of each codeblock for determining its quantization parameter. The experiments validate the improved perceptual quality of decoded images due to the integrated use of the visual distortion sensitivity and the visual attention level in bit allocation. Moreover, the proposed bit allocation method is experimentally shown to yield a substantially higher subjective evaluation score than the other well-known bit allocation methods based on post-compression rate-distortion optimization, saliency maps, foveation of fixations and foveated just-noticeable-difference maps.

Pairwise KLT-Based Compression for Multispectral Images

This paper presents a pairwise KLT-based compression algorithm for multispectral images. Although the KLT has been widely employed for spectral decorrelation, its complexity is high if it is performed on the global multispectral images. To solve this problem, this paper presented a pairwise KLT for spectral decorrelation, where KLT is only performed on two bands every time. First, KLT is performed on the first two adjacent bands and two principle components are obtained. Secondly, one remainning band and the principal component (PC) with the larger eigenvalue is selected to perform a KLT on this new couple. This procedure is repeated until the last band is reached. Finally, the optimal truncation technique of post-compression rate-distortion optimization is employed for the rate allocation of all the PCs, followed by embedded block coding with optimized truncation to generate the final bit-stream. Experimental results show that the proposed algorithm outperforms the algorithm based on global KLT. Moreover, the pairwise KLT structure can significantly reduce the complexity compared with a global KLT.

A Novel Error Resilient Scheme for Wavelet-based Image Coding Over Packet Networks

this paper presents a robust transmission strategy for wavelet based scalable bit stream over packet erasure channel. By taking the advantage of the bit plane coding and the multiple description coding, the proposed strategy adopts layered multiple description coding (LMDC) for the embedded wavelet coders to improve the error resistant capability of the important bit planes in the meaning of D(R) function. Then, the post-compression rate-distortion (PCRD) optimization process is used to improve the overall performance. At decoding, a simple error concealment technique is used to compensate the data loss. The proposed method is applied on Set Partitioning in Hierarchical Trees (SPIHT) coded image and the experimental results show graceful degradation for variable packet erasure rate.

The Analysis and Detection of Double JPEG2000 Compression Based on Statistical Characterization of DWT Coefficients

Detection of double image compression is all the world to the analysis of tampered image and image steganalysis. In order to detect double JPEG2000 compression, through the comparison with JPEG double compression, we analysis the different statistical characterization of DWT coefficients’ frequency histogram under single and double compression because of post compression rate distortion optimization(PCRD-opt algorithm)in JPEG2000 codec. We find a new statistical characterization which is different form double JPEG compression. Under certain conditions, experimental results show that such features can be used to detect whether the JPEG2000 image is double compressed or not.

POST-COMPRESSION RATE-DISTORTION DEVELOPMENT FOR EMBEDDED BLOCK CODING WITH OPTIMAL TRUNCATION IN JPEG2000 IMAGERY

This paper presents a development of the post-compression rate-distortion optimization (PCRD-opt) algorithm in JPEG2000 used for optimal truncation (OT) rate control. The proposed treatment of PCRD-opt differs from the treatment given in the JPEG2000 standard and what is given in a number of publications. The proposed algorithm is implemented in a complete JPEG2000 compression engine as well as the algorithm published in the JPEG2000 standard. The proposed algorithm gives a substantial performance gain, outperforming the implementation given in the standard by 0.25–1 dB in PSNR on average, demonstrating an improvement from the method for PCRD-opt given in the standard. The proposed algorithm is also compared to the JPEG2000 reference implementation, JasPer, and the popular Kakadu JPEG2000 compressor. The proposed algorithm provides equivalent performance results to both JasPer and Kakadu, indicating that the proposed PCRD-opt treatment provides correct OT of JPEG2000 compressed imagery.

Integer-based, post-compression rate-distortion optimization computation in JPEG2000 compression

An integer-based, post-compression rate-distortion optimization (PCRD-Opt) algorithm for JPEG2000 rate control is presented. The distortion estimation, described in the JPEG2000 standard, requires noninteger processing, and the overwhelming computational burden on JPEG2000 is the distortion calculation, which is calculated for every bit of the uncompressed image. An integer-based approach for distortion calculation is proposed. The proposed method reduces the computational requirements for PCRD-Opt within the Tier I encoder, as well as provides a more straightforward algorithm for embedded processing, requiring no distortion lookup tables (LUTs) for proper distortion computation. The proposed integer-based method improves upon the PCRD-Opt method described in the standard. Specifically, the proposed method reduces the Tier I processing time from a direct implementation of PCRD-Opt by approximately 39% on average and reduces the overall JPEG2000 processing by 34%. The proposed method reduces the Tier I processing time from an offline implementation of PDRD-Opt utilizing LUTs by approximately 21% on average, and reduces the overall JPEG2000 processing by 19%. The proposed integer-based distortion estimation provides a rate-distortion curve equivalent to both the direct and offline PCRD methods described in the standard.

Robust Rate-Control for Wavelet-Based Image Coding via Conditional Probability Models

Real-time rate-control for wavelet image coding requires characterization of the rate required to code quantized wavelet data. An ideal robust solution can be used with any wavelet coder and any quantization scheme. A large number of wavelet quantization schemes (perceptual and otherwise) are based on scalar dead-zone quantization of wavelet coefficients. A key to performing rate-control is, thus, fast, accurate characterization of the relationship between rate and quantization step size, the R-Q curve. A solution is presented using two invocations of the coder that estimates the slope of each R-Q curve via probability modeling. The method is robust to choices of probability models, quantization schemes and wavelet coders. Because of extreme robustness to probability modeling, a fast approximation to spatially adaptive probability modeling can be used in the solution, as well. With respect to achieving a target rate, the proposed approach and associated fast approximation yield average percentage errors around 0.5% and 1.0% on images in the test set. By comparison, 2-coding-pass rho-domain modeling yields errors around 2.0%, and post-compression rate-distortion optimization yields average errors of around 1.0% at rates below 0.5 bits-per-pixel (bpp) that decrease down to about 0.5% at 1.0 bpp; both methods exhibit more competitive performance on the larger images. The proposed method and fast approximation approach are also similar in speed to the other state-of-the-art methods. In addition to possessing speed and accuracy, the proposed method does not require any training and can maintain precise control over wavelet step sizes, which adds flexibility to a wavelet-based image-coding system.

Precompression Quality-Control Algorithm for JPEG 2000

In this paper, a precompression quality-control algorithm is proposed. It can greatly reduce computational power of the embedded block coding (EBC) and memory requirement to buffer bit streams. By using the propagation property and the randomness property of the EBC algorithm, rate and distortion of coding passes is approximately predicted. Thus, the truncation points are chosen before actual coding by the entropy coder. Therefore, the computational power, which is measured with the number of contexts to be processed, is greatly reduced since most of the computations are skipped. The memory requirement, which is measured with the amount required to buffer bit streams, is also reduced since the skipped contexts do not generate bit streams. Experimental results show that the proposed algorithm reduces the computational power of the EBC by 80% on average at 0.8 bpp compared with the conventional postcompression rate-distortion optimization algorithm. Moreover, the memory requirement is also reduced by 90%. The average PSNR degrades only about 0.1-0.3 dB, on average.

Rate distortion optimal bit allocation methods for volumetric data using JPEG 2000

Computer modeling programs that generate three-dimensional (3-D) data on fine grids are capable of generating very large amounts of information. These data sets, as well as 3-D sensor/measured data sets, are prime candidates for the application of data compression algorithms. A very flexible and powerful compression algorithm for imagery data is the newly released JPEG 2000 standard. JPEG 2000 also has the capability to compress volumetric data, as described in Part 2 of the standard, by treating the 3-D data as separate slices. As a decoder standard, JPEG 2000 does not describe any specific method to allocate bits among the separate slices. This paper proposes two new bit allocation algorithms for accomplishing this task. The first procedure is rate distortion optimal (for mean squared error), and is conceptually similar to postcompression rate distortion optimization used for coding codeblocks within JPEG 2000. The disadvantage of this approach is its high computational complexity. The second bit allocation algorithm, here called the mixed model (MM) approach, mathematically models each slice's rate distortion curve using two distinct regions to get more accurate modeling at low bit rates. These two bit allocation algorithms are applied to a 3-D Meteorological data set. Test results show that the MM approach gives distortion results that are nearly identical to the optimal approach, while significantly reducing computational complexity.

Efficient rate control for JPEG2000 image coding

JPEG2000 is the new image coding standard which can provide superior rate-distortion performance over the old JPEG standard. However, the conventional post-compression rate-distortion (PCRD) optimization scheme in JPEG2000 is not efficient. It requires entropy encoding all available data even though a large portion of them will not be included in the final output. In this paper, three rate control methods are proposed to efficiently reduce both the computational complexity and memory usage over the conventional PCRD method. The first method, called successive bit-plane rate allocation (SBRA), allocates the bit rate by using the currently available rate-distortion information only. The second method, called priority scanning rate allocation (PSRA), allocates bits according to certain prioritized ordering. The third method uses PSRA to achieve optimal truncation as PCRD without encoding of all the image details and is called priority scanning with optimal truncation (PSOT). Simulation results suggest that the three proposed methods provide different tradeoff among visual quality, computational complexity, coding delay and working memory size. SBRA is memoryless and causal and requires the least computational complexity, lowest coding delay and achieves good visual quality. PSRA achieves higher PSNR than SBRA at the expense of larger working memory size and longer coding delay. PSOT gives the best PSNR but requires even more computation, delay and memory.