Bitplane image coding with parallel coefficient processing

Image coding systems have been traditionally tailored for multiple instruction, multiple data (MIMD) computing. In general, they partition the (transformed) image in codeblocks that can be coded in the cores of MIMD-based processors. Each core executes a sequential flow of instructions to process the coefficients in the codeblock, independently and asynchronously from the others cores. Bitplane coding is a common strategy to code such data. Most of its mechanisms require sequential processing of the coefficients. The last years have seen the upraising of processing accelerators with enhanced computational performance and power efficiency whose architecture is mainly based on the single instruction, multiple data (SIMD) principle. SIMD computing refers to the execution of the same instruction to multiple data in a lockstep synchronous way. Unfortunately, current bitplane coding strategies cannot fully profit from such processors due to inherently sequential coding task. This paper presents bitplane image coding with parallel coefficient (BPC-PaCo) processing, a coding method that can process many coefficients within a codeblock in parallel and synchronously. To this end, the scanning order, the context formation, the probability model, and the arithmetic coder of the coding engine have been re-formulated. The experimental results suggest that the penalization in coding performance of BPC-PaCo with respect to the traditional strategies is almost negligible

Self-Conducted Allocation Strategy of Quality Layers for JPEG2000

The rate-distortion optimality of a JPEG2000 codestream is determined by the density and distribution of the quality layers it contains. The allocation of quality layers is, therefore, a fundamental issue for JPEG2000 encoders, which commonly distribute layers logarithmically or uniformly spaced in terms of bitrate, and use a rate-distortion optimization method to optimally form them. This work introduces an allocation strategy based on the hypothesis that the fractional bitplane coder of JPEG2000 already generates optimal truncation points for the overall optimization of the image. Through these overall optimal truncation points, the proposed strategy is able to allocate quality layers without employing rate-distortion optimization techniques, to self-determine the density and distribution of quality layers, and to reduce the computational load of the encoder. Experimental results suggest that the proposed method constructs near-optimal codestreams in the rate-distortion sense, achieving a similar coding performance as compared with the common PCRD-based approach