Image compression by variable block truncation coding with optimal threshold

Kamel, Mohamed S.; Sun, Chang; Guan, Lixin

doi:10.1109/78.80785

Cited by 48 publications

(16 citation statements)

References 6 publications

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“…In it, BTC stands for the traditional BTC in [1], OBTC the optimal BTC in [2]. We again see significant performance improvement in general.…”

Section: Resultsmentioning

confidence: 74%

“…2 shows the visual perception improvement of MBTC. We see that the blocky artefacts in even the optimal BTC (OBTC) [2] and the high impulse noise in the halftoning-based BTC are effectively mitigated and the final result in MBTC is much closer to the original image.…”

Section: Fig 1 Correlation Between Intensity Information In Originalmentioning

confidence: 76%

“…However, viewing BTC as a two-level quantisation process has been fundamentally limited by the representation power of binary images. As shown in [2], even optimal quantisation still suffers from blocky artefacts for coding blocks of medium size. Recognising the difficulty in the traditional BTC approach and the similarity between BTC and image halftoning, another line of approach to BTC is proposed [3,4], which produces binary images for display also.…”

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confidence: 98%

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Multitone block truncation coding

Yang

Chen

2010

Electron. Lett.

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“…In it, BTC stands for the traditional BTC in [1], OBTC the optimal BTC in [2]. We again see significant performance improvement in general.…”

Section: Resultsmentioning

confidence: 74%

Section: Fig 1 Correlation Between Intensity Information In Originalmentioning

confidence: 76%

mentioning

confidence: 98%

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Multitone block truncation coding

Yang

Chen

2010

Electron. Lett.

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“…Kamel, et al [20] proposed setting an interval, [avg t avg + t ], around the average luminance value of the block to find the best threshold value that minimizes the color mean-square-error. They proceeded to combine this approach with hierarchical BTC.…”

Section: Binarypattern Image Codingmentioning

confidence: 99%

<title>Feasibility of video codec algorithms for software-only playback</title>

Rodriguez

Morse

1994

Digital Video Compression on Personal Computers: Algorithms and Technologies

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Software-only video codecs can provide good playback performance in desktop computers with a 486 or 68040 CPU running at 33 MHz without special hardware assistance. Typically, playback of compressed video can be categorized into three tasks: the actual decoding of the video stream, color conversion, and the transfer ofdecoded video data from system RAM to video RAM. By current standards, good playback performance is the decoding and display of video sireams of 320 by 240 (orlarger) compressed frames at 15 (or greater) frames-per-second. Software-only video codecs have evolved by modifying and tailoring existing compression methodologies to suit video playback in desktop computers. In this paper we examine the characteristics used to evaluate software-only video codec algorithms, namely: image fidelity (i.e., image quality), bandwidth (i.e., compression), ease-ofdecoding (i.e., playback performance), memory consumption, compression to decompression asymmetry, scalability, and delay. We discuss the tradeoffs among these variables and the compromises that can be made to achieve low numerical complexity for software-only playback. Frame-thiferencing approaches are described since software-only video codecs typically employ them to enhance playback performance. To complement other papers that appear in this session of the Proceedings, we review methods derived from binarypattern image coding since these methods are amenable for software-only playback. In particular, we inroduce a novel approach called pixel distribution image coding. L INTRODUCTIONDigital video in desktop computers currently consists of two categories of video codecs (compressor/decompressors). The first category consists of video coding algorithms that exhibit low complexity for playback and therefore produce compressed video streams that can be decoded and displayed in desktop computers without special hardware assistance -the compute?s CPU performs all of the decompression and display tasks. This set of video codec algorithms is typically referred to as algorithms amenable for software-only video playback, or software-only video codecs. The side effect of low playback complexity algorithms is that they tend to exhibit limited image quality. The second category of video codecs in desktop computers is typically referred to as hardware-assisted video codecs. Like the video coding algorithm described by the Moving Pictures Expert Group (MPEG) [1], hardware-assisted codecs are capable of providing a substantial increase in image quality in comparison to software-only video codecs. Figure 1 depicts the image quality versus playback complexity space spanned by the two sets of video codecs. Notice that software-only video codecs are within incremental quality of each other. An imaginary horizontal line above the domain spanned by the software-only video codecs reminisces the limited quality they provide. Likewise, an imaginary vertical line to the left of the domain of hardware-assisted codecs, indicates that these algorithms are too complex for software-o...

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“…Such as variable block truncation coding with optimal threshold, where the image is divided into variable size blocks rather than fixed size, and an optimal threshold is adopted to minimize the mean square error [3]; using a set of predefined bit planes to independently encode image, where the Huffman coding is also adopted to further reduce the bit rate [4]; adopting universal Hamming codes and a differential pulse code modulation (PCM) to the bit plane and the side information of the BTC to reduce bit rate and preserving the low computational complexity [5]; using a hybrid method by combining BTC, Vector Quantization (VQ), and modified Genetic Algorithm (GA) to achieve better representability and generalization than conventional BTC [6]. These studies proposed good solutions in quality or coding gain improvement.…”

Section: Introductionmentioning

confidence: 99%

Hybrid block truncation coding for color image compression

Wang

Jeung

Chong

2009

2009 IEEE International Conference on Network Infrastructure and Digital Content

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In this paper, a hybrid block truncation coding (HBTC) is presented for color image compression. In the HBTC algorithm to improve the compression ratio of the basic BTC, only luminance bit-map is employed to represent the edge information of the coding block. Moreover, an efficient previous proposed algorithm, adaptive quantization coding (AQC), is used to compress the two representative levels further. Simulation results show that the proposed HBTC performs as well as the BTC in terms of subject visual quality, and significantly improves the compression ratio of BTC from 2.88:1 to 6.00:1 with the limited performance losing about 0.66dB in PSNR.

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Image compression by variable block truncation coding with optimal threshold

Cited by 48 publications

References 6 publications

Multitone block truncation coding

Multitone block truncation coding

<title>Feasibility of video codec algorithms for software-only playback</title>

Hybrid block truncation coding for color image compression

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