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With a rapid increase of image resolution in recent mobile video systems, the memory bandwidth and power consumption have surfaced as critical problems in video coding. Despite many embedded compression algorithms proposed to overcome these problems, no proper algorithms have yet been reported with high enough throughput and no quality loss. This p...
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... the proposed architecture supports both encod- ing and decoding, only the pipeline stage of the decoder is explained in this paper because the decoder is invoked more often than the encoder in the video coding system. In the pipeline stage of the proposed architecture shown in Fig.4, the DC and the header information of the encoded bit stream is unpacked first. ...
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... Image compression is intended to eliminate the number of bits required to represent an image. Lossless image compression is determined by the low compression ratio while in lossy compression algorithms the coded image acquires a high compression ratio based on human visual properties [6,7]. In [8] the compression-based transformation has a low computational complexity and capable of accumulating the lowest number of coefficients of signal energy. ...
A color image compression is the most challenging task in the field of multimedia. During last decades several techniques are developed for improving the quality, coding time and compression ratio using different coding strategies. In this work, an effective compression method for hybrid images is proposed based on the discrete wavelet transformation and hybrid encoding algorithm (Huffman and SPIHT). This paper's primary participation is to take advantage of the hybrid encoding technique to maintain the quality of the reconstructed image and the reduction of time complexity. The sample test images are taken from both standard image database and high-quality images (SD and HD). The performance of the proposed scheme is evaluated by using different metrics such as (PSNR, compression ratio and encoding time). Test results indicate that the time and compression ratio of encoding are improved in the expense of the image quality.
... In many LEC methods, Golomb algorithms or Golomb-Rice algorithms are used for entropy coding [8,12,13,15,25,35]. Golomb-Rice coding divides a positive integer (an input value) into two parts: quotient q and remainder r. ...
This paper proposes a high-throughput lossless image-compression algorithm based on Golomb–Rice coding and its hardware architecture. The proposed solution increases compression ratios (CRs) while preserving the throughput by taking advantage of a novel parallel variable-length sign coding (PVSC) algorithm that reduces the sign bits to achieve a higher CR. In addition, the proposed solution adopts and modifies the two existing compression algorithms to improve the overall compression performance. The experimental results show that the proposed solution yields an average CR of 3.12, which is higher than those achieved with the previous algorithms. The hardware implementation of the proposed solution for an 8 × 8 block unit achieves a throughput of 18 GBps and 24 GBps when encoding and decoding, respectively. This hardware performance is enough to handle 7680×4320@240-Hz image processing.
... Therefore, video compression algorithms use many techniques and concepts of image compression algorithms, like JPEG (joint photographic expert group). [5] Compression has two types named lossless and lossy. [1] Unnecessary information is removed to reduce bit in lossy compression. ...
... So, from this functionality there are three kinds of frames can be generated from group of picture: Iframe, Pframe and Bframe. [5] ...
... Thus only portions of a frame that moves or blocks of a frame that can be borrowed from other blocks in previous frames in video, are coded with fewer bits. For this purpose, 16x16 macro blocks are divided into the 8x8 pixel blocks.[2] [5] Some macro blocks are same as previous macro block means they do not change. These are not recoded in subsequent frames to saving size. ...
... [2]) are usually software oriented and are too complex for efficient hardware implementation. Many have proposed VLSI oriented lossless compression techniques that are tailormade for video signals [3][4][5][6][7][8][9][10][11]. These techniques perform well when there is correlation among adjacent pixels (in images and video streams) but might yield higher bit rate at their output if such correlation does not exist. ...
... To the best of our knowledge, ViLoCoN is the most lightweight lossless video codec that has been described in literature (5.4K NAND gates, ~23% less than the second most lightweight codec [3]). Moreover, it introduces high compression ratio that is higher by ~31% than its most lightweight predecessor [3] and is comparable to codecs that demand about one order of magnitude more gates (including memory hardware requirements) [4][5][6][7][8][9][10][11]. ...
... Upper limit (10,10) Lower limit (-9,-10) ...
A novel lossless image and video codec termed ViLoCoN is presented. ViLoCoN stands for Video Lossless Compression for NoCs (i.e. Networks-on-chip) as it is highly applicable to reduce power consumption and bandwidth of on-chip and inter chip interconnect in modern multimedia SoCs. ViLoCoN's encoder/decoder use fewer gates (71% and 84%) as compared to previous lightweight encoders and decoders, respectively, and provide a higher compression ratio (by ~31%) on average, as compared to the most lightweight predecessor. ViLoCoN's performance is comparable to well known codecs that demand one order of magnitude more hardware resources.
... ZhihaiHenryHe, vol. 17, no. 4, April 2010), (Jaemoon Kim, Jungsoo Kim andChong-Min Kyung , 978-1-4244-4291 / 09 2009 IEEE. ICME 2009), image compression is one of the most used techniques in the field of image processing. ...
... Wavelet transformation (WT) [1], [2]- [7], vector quantization (VQ) [8] and different encoding approaches are generally used in addition to numerous other methods in image compression. The problem in lossless compression method is that, the compression ratio is very less; where as in the lossy compression the compression ratio is very high but the quality of the image is lost. ...
This paper presents a new approach of edge preserving and edge based segmentation for compression of images using Modified Fast Haar wavelet transform (MFHW) and Bit Plane Encoder to elevate the compression ratio with high picture quality. The edges of an image are preserved to increase the PSNR, and then the detected edges are used to segment the foreground and background images. The Foreground of the image is given more importance than the background images. A wavelet transform is used to extract the redundant information at low frequency and a matching Bit Plane encoder is used to code the segments of the image at different quality levels. The Proposed method highly preserves quality of the foreground image. Normal compression algorithms will not preserve the high frequency details such as edges, corners etc., in this method edges are preserved and used for segmenting the layers of the original image. The two level Fast haar Wavelet transform is used to decompose the image at different frequency levels, which has high multi-resolution characteristics. The proposed method increases both the compression ratio and PSNR. .
... Wavelet transformation(WT) [1], [5]-[10], vector quantization(VQ) [4],[5] approaches are generally used in addition to numerous other methods[11]-[17] in image compression. The problem in lossless compression method is that, the compression ratio is very less; where as in the lossy compression the compression ratio is very high but may loose vital information of the image. ...
... Wavelet transformation(WT) [1], [5]-[10], vector quantization(VQ) [4],[5] approaches are generally used in addition to numerous other methods[11]-[17] in image compression. The problem in lossless compression method is that, the compression ratio is very less; where as in the lossy compression the compression ratio is very high but may loose vital information of the image. ...
A hybrid image compression method is proposed in this paper which segments the image intobackground and foreground and compress them with different quality levels.. The foreground of the imageis given more importance than the background. An edge based segmentation method is used to segment theimage into foreground area and background area. The proposed method highly preserves quality of theforeground image. JPEG compression is a widely used compression technique. Normally the JPEGcompression method uses linear quantization and threshold values to maintain certain quality level in anentire image. The proposed method adapts variable quantization and threshold values corresponding tobackground and foreground. This ensures that the vital area of the image is highly preserved than the otherareas of the image. This hybrid approach increases the compression ratio and produces a desired highquality compressed image.
