3,589 research outputs found

    Variable size block truncation coding with adaptive bit plane omission for image compression

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    A modified version of the Block Truncation Coding (BTC), which is a non-information preserving image compression technique, is studied. The first modification is the introduction of variable block sizes to the standard BTC technique. The second modification is the adaptive omission of bit planes. Threshold selections for this modified BTC technique are analyzed in the context of the human visual system. Modified BTC techniques are compared against the standard technique from the point of view of visual image quality and compresion efficiency

    A VLSI architecture of JPEG2000 encoder

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    Copyright @ 2004 IEEEThis paper proposes a VLSI architecture of JPEG2000 encoder, which functionally consists of two parts: discrete wavelet transform (DWT) and embedded block coding with optimized truncation (EBCOT). For DWT, a spatial combinative lifting algorithm (SCLA)-based scheme with both 5/3 reversible and 9/7 irreversible filters is adopted to reduce 50% and 42% multiplication computations, respectively, compared with the conventional lifting-based implementation (LBI). For EBCOT, a dynamic memory control (DMC) strategy of Tier-1 encoding is adopted to reduce 60% scale of the on-chip wavelet coefficient storage and a subband parallel-processing method is employed to speed up the EBCOT context formation (CF) process; an architecture of Tier-2 encoding is presented to reduce the scale of on-chip bitstream buffering from full-tile size down to three-code-block size and considerably eliminate the iterations of the rate-distortion (RD) truncation.This work was supported in part by the China National High Technologies Research Program (863) under Grant 2002AA1Z142

    Hierarchical morphological segmentation for image sequence coding

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    This paper deals with a hierarchical morphological segmentation algorithm for image sequence coding. Mathematical morphology is very attractive for this purpose because it efficiently deals with geometrical features such as size, shape, contrast, or connectivity that can be considered as segmentation-oriented features. The algorithm follows a top-down procedure. It first takes into account the global information and produces a coarse segmentation, that is, with a small number of regions. Then, the segmentation quality is improved by introducing regions corresponding to more local information. The algorithm, considering sequences as being functions on a 3-D space, directly segments 3-D regions. A 3-D approach is used to get a segmentation that is stable in time and to directly solve the region correspondence problem. Each segmentation stage relies on four basic steps: simplification, marker extraction, decision, and quality estimation. The simplification removes information from the sequence to make it easier to segment. Morphological filters based on partial reconstruction are proven to be very efficient for this purpose, especially in the case of sequences. The marker extraction identifies the presence of homogeneous 3-D regions. It is based on constrained flat region labeling and morphological contrast extraction. The goal of the decision is to precisely locate the contours of regions detected by the marker extraction. This decision is performed by a modified watershed algorithm. Finally, the quality estimation concentrates on the coding residue, all the information about the 3-D regions that have not been properly segmented and therefore coded. The procedure allows the introduction of the texture and contour coding schemes within the segmentation algorithm. The coding residue is transmitted to the next segmentation stage to improve the segmentation and coding quality. Finally, segmentation and coding examples are presented to show the validity and interest of the coding approach.Peer ReviewedPostprint (published version

    Image coding using wavelet transform and adaptive block truncation coding

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    This thesis presents a new image coding using wavelet transform and adaptive block truncation coding. Images are first pre-processed by the wavelet transform and then coded by the adaptive block truncation coding. Algorithms for both monochrome and color images are proposed and experimentally studied. The adaptive block truncation coding is also modified to achieve better performance. For coding monochrome images at the bit-rate region between 0.8 to 1.2 bits/pixel, the performance of the new coding is comparable to the ones of subband codings and other image codings using the wavelet transform; however, the new coding offers less computational load. The new coding also gives a good reconstruction of a color image at the bit-rate of 1.0 bit/pixel. The comparison between the new coding and the original adaptive block truncation coding is also given. The discussion on effects of a filter and a number of decomposition levels used for an implementation of the wavelet transform is included in this thesis, as well

    Mathematical transforms and image compression: A review

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    It is well known that images, often used in a variety of computer and other scientific and engineering applications, are difficult to store and transmit due to their sizes. One possible solution to overcome this problem is to use an efficient digital image compression technique where an image is viewed as a matrix and then the operations are performed on the matrix. All the contemporary digital image compression systems use various mathematical transforms for compression. The compression performance is closely related to the performance by these mathematical transforms in terms of energy compaction and spatial frequency isolation by exploiting inter-pixel redundancies present in the image data. Through this paper, a comprehensive literature survey has been carried out and the pros and cons of various transform-based image compression models have also been discussed

    Combined effect of neolamarckia cadamba leaves and electroporation method on hela cell anti- proliferation process

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    This study suggests that natural sources may become an important tool in treating cancer. Neolamarckia cadamba (NC) leaves also well-known as “Anthocephalus Cadamba”, is a precious plant in Ayurvedic medicine. HeLa cells are one of the examples of eukaryotic cells type. It is derived from human cervical cancer cells. This experiment is conducted in different concentrations of NC Leaves (1μg/ml, 5μg/ml, 10μg/ml, 20μg/ml, 30μg/ml, 40μg/ml, 50μg/ml, 60μg/ml, 70μg/ml, 80μg/ml, 90μg/ml and 100μg/ml) for 48 hours. This experiment’s result proves that the anti-cancer properties of the extract of NC leaves are by increasing the concentration of extract, the numbers of cell viability will decrease. For contribution, the process of NC leaves extract will be combined with the electroporation process to investigate the effect on HeLa cell. Electroporation parameters used for this study were (voltage 600v/cm, pulse duration 5ms, single pulse)
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