Wavelet Based Embedded Image Coding Using Unified Zero-Block-Zero-Tree Approach

Moinuddin, Athar Ali; Khan, E.

doi:10.1109/icassp.2006.1660377

Cited by 11 publications

(13 citation statements)

References 7 publications

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“…It is noteworthy that our method without arithmetic coding is comparable and even superior to SPECK-AC, SPIHT-AC and JPEG2000. Table 4 shows the PSNR performances of EZBC [8], SMPAOET_SPIHT [4], WBTC [9] and WZBC without arithmetic coding. From the table, we can see that WZBC is superior to EZBC, SMPAOET_SPIHT and WBTC.…”

Section: Numerical Resultsmentioning

confidence: 99%

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Using a weighted zeroblock coder for satellite image compression

Xiao

Shi

et al. 2010

J. Appl. Remote Sens

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In this paper, we propose an embedded satellite image compression method using Weighted ZeroBlock Coding (WZBC) and optimal sorting. In order to reduce average codeword length, Set Partition Embedded block (SPECK) and Embedded ZeroBlock Coder (EZBC) both encode significant block-sets with fixed-length bits, while WZBC assigns different-length bits to encode block-sets which contain different numbers of significant subblocks. In view of the context correlation among coefficients/blocks, WZBC employs a weight context to optimize the scanning order of the significance testing and the ratedistortion performance. Experimental results show that the proposed WZBC in binary coding mode provides excellent coding performance compared with those of SPECK and Set Partitioning In Hierarchical Trees (SPIHT) which use arithmetic coding, and can even closely approach that of JPEG2000. When arithmetic coding is extensively used, the proposed method has clear advantages.

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Section: Numerical Resultsmentioning

confidence: 99%

“…In 2006, wavelet based embedded image coding using unified zero-block-zerotree approach [9] is proposed. The combination of zero-block and zero-block can break the searching restrict of block boundary, reference [9] shows the performance of the method is higher than that of SPIHT and SPECK.…”

Section: Introductionmentioning

confidence: 99%

Using a weighted zeroblock coder for satellite image compression

Xiao

Shi

et al. 2010

J. Appl. Remote Sens

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“…SPIHT especially has inspired thousands of attempts to improve upon the original work [41]. One such successful attempt is the block-tree approach of Moinuddin and Khan [33]. Articles by Wheeler and Pearlman [52] and Shively et al [47] report the use of fixed memory arrays to store the states of pixels and sets, thereby alleviating the memory problem.…”

Section: Resultsmentioning

confidence: 99%

Wavelet Image Compression

Pearlman¹

2013

Synthesis Lectures on Image, Video, and Multimedia Processing

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“…3). De hecho, el algoritmo desarrollado unifica en el mismo sistema aspectos localizados de manera discreta en sistemas de compresión previos, como por ejemplo SPIHT (Set Partitioning in Hierarchical Trees) (Said and Pearlman, 1996), SPECK (Set Partioning Embedded Block Coder) (Pearlman et al, 2004), HBC (Hybrid Block Coder) (Wheeler and Pearlman, 2000), y WBTC (Wavelet Block Tree Coding) (Moinuddin and Khan, 2006), permitiendo, de una forma paramétrica, ajustar las condiciones de trabajo y adaptarse mejor al medio de comunicación existente.…”

Section: El Algoritmo Depth Embedded Block Tree (Debt)unclassified

Sistema de Visión Subacuático Inalámbrico Usando un Algoritmo de Compresión Progresivo con Región de Interés

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Centelles

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et al. 2017

Rev. iberoam. autom. inform. ind.

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ResumenLa creciente demanda en todo el mundo de sistemas de intervención submarina en diversos dominios de aplicación requiere sistemas más versátiles y económicos. Empleando un sistema de comunicación inalámbrica, los robots semiautónomos supervisados disponen de libertad de movimientos y, al mismo tiempo, permiten al operador obtener información visual y supervisar la intervención. Por otro lado, la velocidad de transmisión de datos típica de los canales inalámbricos submarinos es, en general, muy limitada, siendo necesaria la aplicación de técnicas de compresión avanzadas. En este artículo se presenta principalmente el algoritmo DEBT (Depth Embedded Block Tree) para la compresión progresiva de imágenes con región de interés (ROI). Los resultados demuestran ventajas con respecto a otros algoritmos de compresión, y la posibilidad de ejecución del algoritmo en tiempo real en ordenadores embebidos de bajo consumo basados en ARM. Palabras Clave: Compresión de Imagen, Transmisión de Datos, Sistemas de Comunicación, Teleoperación Underwater Wireless Vision System Using Progressive Image Compression and Region of Interest AbstractThe increasing demand for underwater robotic intervention systems around the world in several application domains requires more versatile and inexpensive systems. By using a wireless communication system, supervised semi-autonomous robots have freedom of movement and, at the same time, allows the operator to get camera feedback and supervise the intervention. On the other hand, the typical data rate of the wireless submarine channels is generally very limited, requiring the application of advanced compression techniques. In this paper we present the DEBT (Depth Embedded Block Tree) algorithm for the progressive compression of images with region of interest (ROI). The results demonstrate advantages with other compression algorithms, and the possibility of executing the algorithm in real time on ARM-based embedded low-power computers.

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Wavelet Based Embedded Image Coding Using Unified Zero-Block-Zero-Tree Approach

Cited by 11 publications

References 7 publications

Using a weighted zeroblock coder for satellite image compression

Using a weighted zeroblock coder for satellite image compression

Wavelet Image Compression

Sistema de Visión Subacuático Inalámbrico Usando un Algoritmo de Compresión Progresivo con Región de Interés

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