Sample-Parallel Execution of EBCOT in Fast Mode

JPEG 2000’s most computationally expensive building block is the Embedded Block Coder with Optimized Truncation (EBCOT). This paper evaluates how encoders targeting a parallel architecture such as a GPU can increase their throughput in use cases where very high data rates are used. The compression efficiency in the less significant bit-planes is then often poor and it is beneficial to enable the Selective Arithmetic Coding Bypass style (fast mode) in order to trade a small loss in compression efficiency for a reduction of the computational complexity. More importantly, this style exposes a more finely grained parallelism that can be exploited to execute the raw coding passes, including bit-stuffing, in a sample-parallel fashion. For a latency- or memory critical application that encodes one frame at a time, EBCOT’s tier-1 is sped up between 1.1x and 2.4x compared to an optimized GPU-based implementation. When a low GPU occupancy has already been addressed by encoding multiple frames in parallel, the throughput can still be improved by 5% for high-entropy images and 27% for low-entropy images. Best results are obtained when enabling the fast mode after the fourth significant bit-plane. For most of the test images the compression rate is within 1% of the original

Técnicas de compresión de imágenes hiperespectrales sobre hardware reconfigurable

Tesis de la Universidad Complutense de Madrid, Facultad de Informática, leída el 18-12-2020Sensors are nowadays in all aspects of human life. When possible, sensors are used remotely. This is less intrusive, avoids interferces in the measuring process, and more convenient for the scientist. One of the most recurrent concerns in the last decades has been sustainability of the planet, and how the changes it is facing can be monitored. Remote sensing of the earth has seen an explosion in activity, with satellites now being launched on a weekly basis to perform remote analysis of the earth, and planes surveying vast areas for closer analysis...Los sensores aparecen hoy en día en todos los aspectos de nuestra vida. Cuando es posible, de manera remota. Esto es menos intrusivo, evita interferencias en el proceso de medida, y además facilita el trabajo científico. Una de las preocupaciones recurrentes en las últimas décadas ha sido la sotenibilidad del planeta, y cómo menitoirzar los cambios a los que se enfrenta. Los estudios remotos de la tierra han visto un gran crecimiento, con satélites lanzados semanalmente para analizar la superficie, y aviones sobrevolando grades áreas para análisis más precisos...Fac. de InformáticaTRUEunpu

Evaluation of GPU/CPU Co-Processing Models for JPEG 2000 Packetization

With the bottom-line goal of increasing the throughput of a GPU-accelerated JPEG 2000 encoder, this paper evaluates whether the post-compression rate control and packetization routines should be carried out on the CPU or on the GPU. Three co-processing models that differ in how the workload is split among the CPU and GPU are introduced. Both routines are discussed and algorithms for executing them in parallel are presented. Experimental results for compressing a detail-rich UHD sequence to 4 bits/sample indicate speed-ups of 200x for the rate control and 100x for the packetization compared to the single-threaded implementation in the commercial Kakadu library. These two routines executed on the CPU take 4x as long as all remaining coding steps on the GPU and therefore present a bottleneck. Even if the CPU bottleneck could be avoided with multi-threading, it is still beneficial to execute all coding steps on the GPU as this minimizes the required device-to-host transfer and thereby speeds up the critical path from 17.2 fps to 19.5 fps for 4 bits/sample and to 22.4 fps for 0.16 bits/sample

A Real Time Image Processing Subsystem: GEZGIN

In this study, a real-time image processing subsystem, GEZGIN, which is currently being developed for BILSAT-1, a 100kg class micro-satellite, is presented. BILSAT-1 is being constructed in accordance with a technology transfer agreement between TÜBITAK-BILTEN (Turkey) and SSTL (UK) and planned to be placed into a 650 km sunsynchronous orbit in Summer 2003. GEZGIN is one of the two Turkish R&D payloads to be hosted on BILSAT-1. One of the missions of BILSAT-1 is constructing a Digital Elevation Model of Turkey using both multi-spectral and panchromatic imagers. Due to limited down-link bandwidth and on-board storage capacity, employment of a realtime image compression scheme is highly advantageous for the mission. GEZGIN has evolved as an implementation to achieve image compression tasks that would lead to an efficient utilization of both the down-link and on-board storage. The image processing on GEZGIN includes capturing of 4-band multi-spectral images of size 2048x2048 8- bit pixels, compressing them simultaneously with the new industry standard JPEG2000 algorithm and forwarding the compressed multi-spectral image to Solid State Data Recorders (SSDR) of BILSAT-1 for storage and down-link transmission. The mission definition together with orbital parameters impose a 6.5 seconds constraint on real-time image compression. GEZGIN meets this constraint by exploiting the parallelism among image processing units and assigning compute intensive tasks to dedicated hardware. The proposed hardware also allows for full reconfigurability of all processing units

Context-adaptive binary arithmetic coding with fixed-length codewords

Context-adaptive binary arithmetic coding is a widespread technique in the field of image and video coding. Most state-of-the-art arithmetic coders produce a (long) codeword of a priori unknown length. Its generation requires a renormalization procedure to permit progressive processing. This paper introduces two arithmetic coders that produce multiple codewords of fixed length. Contrary to the traditional approach, the generation of fixed-length codewords does not require renormalization since the whole interval arithmetic is stored in the coder's internal registers. The proposed coders employ a new context-adaptive mechanism based on variable-size sliding window that estimates with high precision the probability of the symbols coded. Their integration in coding systems is straightforward as demonstrated within the framework of JPEG2000. Experimental tests indicate that the proposed coders are computationally simpler than the MQ coder of JPEG2000 and the M coder of HEVC while achieving superior coding efficiency

Multiprocessor DSP Implementation of the JPEG 2000 Codec

The transition to JPEG2000 from other image formats such as standard JPEG offers im proved compression and image quality, yet has not been widely adopted in practice. This is mainly due to the complexity of the JPEG2000 algorithm. Standard JPEG uses the Discrete Cosine Transform (DCT) and Huffmann encoding to achieve its compression, whereas JPEG2000 uses the wavelet transform and arithmetic encoding. Due to the wide acceptance of JPEG, there are processors such as Equator Technology\u27s BSP-15 digital signal processor (DSP) that have been designed with features specifically for JPEG appli cations. For some of the current digital printing applications where JPEG is used, images must be encoded and decoded at rates exceeding 100 pages per minute. A multiprocessor environment consisting of Equator Technology\u27s BSP-15 processors may offer acceptable performance for the JPEG2000 codec. The aim of this work is to design a JPEG2000 codec for the BSP-15 processor and to determine if this processor is capable of delivering the performance required by high end digital printers. The features of the BSP-15 that are well suited for the JPEG2000 algorithm will be discussed, as well as future improvements that could be incorporated into the architecture. By analyzing the advantages and disadvantages of this processor, the next generation of processors may be able to offer features that will allow it to excel in JPEG2000 processing. A multiprocessor DSP implementation of the JPEG2000 codec is the main result of this work. The resulting codec is able to provide more than double the processing throughput of existing JPEG2000 software

LOCO-ANS: An Optimization of JPEG-LS Using an Efficient and Low-Complexity Coder Based on ANS

Near-lossless compression is a generalization of lossless compression, where the codec user is able to set the maximum absolute difference (the error tolerance) between the values of an original pixel and the decoded one. This enables higher compression ratios, while still allowing the control of the bounds of the quantization errors in the space domain. This feature makes them attractive for applications where a high degree of certainty is required. The JPEG-LS lossless and near-lossless image compression standard combines a good compression ratio with a low computational complexity, which makes it very suitable for scenarios with strong restrictions, common in embedded systems. However, our analysis shows great coding efficiency improvement potential, especially for lower entropy distributions, more common in near-lossless. In this work, we propose enhancements to the JPEG-LS standard, aimed at improving its coding efficiency at a low computational overhead, particularly for hardware implementations. The main contribution is a low complexity and efficient coder, based on Tabled Asymmetric Numeral Systems (tANS), well suited for a wide range of entropy sources and with simple hardware implementation. This coder enables further optimizations, resulting in great compression ratio improvements. When targeting photographic images, the proposed system is capable of achieving, in mean, 1.6%, 6%, and 37.6% better compression for error tolerances of 0, 1, and 10, respectively. Additional improvements are achieved increasing the context size and image tiling, obtaining 2.3% lower bpp for lossless compression. Our results also show that our proposal compares favorably against state-of-the-art codecs like JPEG-XL and WebP, particularly in near-lossless, where it achieves higher compression ratios with a faster coding speedThis work was supported in part by the Spanish Research Agency through the Project AgileMon under Grant AEI PID2019-104451RB-C2