An image compression model via adaptive vector quantization: hybrid optimization algorithm

Chavan, Pratibha; Rani, B. Sheela; Murugan, M.; Chavan, Pramod U.

doi:10.1080/13682199.2022.2141873

Cited by 3 publications

(4 citation statements)

References 28 publications

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“…In 2023, Chavan et al [13] reported an analysis of codebook optimization for image compression using EA. This study examines the codebook optimization of VQ using the modified GA, and PSO.…”

Section: Literature Reviewmentioning

confidence: 99%

A Codebook Compression Method for Vector Quantization Algorithm

Abul Hasnat,

Dibyendu Barman,

Md Azizul Hoque

et al. 2024

Proc. eng. technol. innov.

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This study introduces a novel approach to enhance the compression ratio of the vector quantization (VQ) algorithm by specifically targeting the compression of its codebook. The VQ algorithm typically generates an index matrix and a codebook to represent compressed images. The proposed method focuses on reducing the size of the codebook, which comprises N codewords, each with elements quantized into four levels. Each 8-bit element in a codeword is compressed to 2-bits, and the encoded codeword is accompanied by the minimum value and a threshold value in the codebook. Experimental results on benchmark color images, such as baboon, airplane, Lena, and others, demonstrate a significant reduction of 62.50% in the size of the VQ codebook.

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Section: Literature Reviewmentioning

confidence: 99%

A Codebook Compression Method for Vector Quantization Algorithm

Abul Hasnat,

Dibyendu Barman,

Md Azizul Hoque

et al. 2024

Proc. eng. technol. innov.

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“…The hiding capacity is identified by the number of bits, while the imperceptibility is identified by image quality. To assess image quality, the commonly used parameter is the peak signal-to-noise ratio (PSNR) as defined in Equation (11).…”

Section: The Environment and Parametersmentioning

confidence: 99%

“…This is due to the fact that computing is simple and inexpensive. There are several widely used compression methods, including vector quantization (VQ) [9][10][11][12], block truncation coding (BTC) [13][14][15][16], AMBTC [17,18], and JPEG compression [19][20][21], beginning with Delp and Mitchell [13] in 1979, who proposed block truncation coding (BTC) for image compression, and then further developed in 1984 by Lema and Mitchell [17], whose method is known as absolute moment block truncation coding (AMBTC). AMBTC offers simpler computation than BTC and acquires better image quality.…”

Section: Introductionmentioning

confidence: 99%

High Imperceptible Data Hiding Method Based on Combination Theory for AMBTC Compressed Images

Anggriani

Chiou

et al. 2023

Applied Sciences

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The rapid development of digital multimedia has resulted in a massive storm of large-scale data. The data compression method reduces data size and lowers transmission costs. As a result, data-hiding research in the compression domain poses significant challenges to researchers. This work proposes a highly imperceptible data-hiding scheme for a compressed absolute moment block truncation coding (AMBTC) image. The proposed method addresses the shortcomings of the current block-based AMBTC data-hiding scheme, with an incredibly complex block as non-embedding. This is because embedding in complex blocks causes substantial distortions in the image, resulting in low imperceptibility performance. Combination theory was implemented to ensure the high imperceptibility of the modified compressed images. The experimental findings proved that the proposed method achieved high imperceptibility and high hiding capacity by modifying one pixel in a block to embed confidential bits.

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“…This is due to the fact that computing is simple and inexpensive. There are several widely used compression methods, including vector quantization (VQ) [6]- [8], block truncation coding (BTC) [9]- [12], AMBTC [13], and JPEG compression [14]- [16]. Beginning by Delp and Mitchell [9] in 1979 which proposed block truncation coding (BTC) for image compression.…”

Section: Of 12mentioning

confidence: 99%

High Imperceptible Data Hiding Method for AMBTC Compressed Images Based on Combination Theory

Anggriani¹,

Chiou²,

Wu³

et al. 2023

Preprint

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The rapid development of digital multimedia has resulted in a massive storm of large-scale data. The data compression method reduces data size and lowers transmission costs. As a result, data-hiding research in the compression domain poses significant challenges to researchers. This paper proposes a highly imperceptible data-hiding scheme for a compressed image of Absolute Moment Block Truncation Coding (AMBTC). The combination theory is implemented to ensure the high imperceptibility of the modified compressed images. By only modifying one pixel in a block to embed secret bits, the experimental results show that the proposed method achieved high imperceptibility and high hiding capacity.

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An image compression model via adaptive vector quantization: hybrid optimization algorithm

Cited by 3 publications

References 28 publications

A Codebook Compression Method for Vector Quantization Algorithm

A Codebook Compression Method for Vector Quantization Algorithm

High Imperceptible Data Hiding Method Based on Combination Theory for AMBTC Compressed Images

High Imperceptible Data Hiding Method for AMBTC Compressed Images Based on Combination Theory

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