EBTC: An economical method for searching the threshold of BTC compression

Yang, Ching-Yung; Lin, Ja‐Chen

doi:10.1049/el:19961267

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…Thirteen well known gray-scale images, each with 256 ϫ256 pixels and 8 bits/pixel resolution are tested on a PC 11 AMBTC, 7 and MMSEQ 1 algorithms are implemented. Fuzzy clustering is performed with the threshold value ⑀ set to 10 Ϫ3 .…”

Section: Resultsmentioning

confidence: 99%

“…8 Other techniques are also proposed to find the optimal threshold for BTC using MSE as a fidelity criterion. [9][10][11] Due to its relatively high bit rate, different variants of BTC aimed at reducing the bit rate using median filtering, 12 discrete cosine transform, 13 or interpolation 14 are proposed. These improvements, however, are achieved at the cost of decreasing image quality.…”

mentioning

confidence: 99%

“…Obviously, the mean of the total pixel values is not an optimal threshold in the sense of minimizing MSE. Furthermore, thresholds generated by BTC 1 and its variants 7,[9][10][11] are difficult ones. Indeed, these thresholds may retain sharp edges, and this leads to artifacts such as the staircase effect, while edge regions are not always sharp but smooth ones.…”

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confidence: 99%

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Fuzzy block truncation coding

Boudraa

Beghdadi

Dehak³

et al. 2002

Opt. Eng

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Block truncation coding (BTC) is a well known lossy compression scheme. Due to its low complexity and easy implementation, BTC has gained wide interest in its further development and application for image compression. Based on simple thresholding, BTC retains sharp edges and thus leads to artifacts such as the staircase effect. The second problem encountered in BTC is the splitting of homogeneous regions, which produces false contours. In this work a fuzzy approach of BTC to avoid truncating homogeneous blocks and to preserve smooth edges in two-cluster blocks is proposed. Each image block, viewed as a fuzzy set, is segmented into two clusters using a fuzzy clustering algorithm. The block is then encoded by modified fuzzy weighted means of the two clusters. Initialization strategies of the fuzzy clustering algorithm and a contextual quantization method are proposed. Experimental results show an improvement of visual quality of reconstructed images and peak signal-to-noise ratio when compared to BTC, economical BTC (EBTC), absolute moment BTC (AMBTC), and a minimum mean square error quantizer (MMSEQ). Computation time required by AMBTC, EBTC, and fuzzy BTC methods are reported.

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Fuzzy block truncation coding

Boudraa

Beghdadi

Dehak³

et al. 2002

Opt. Eng

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“…Thereafter, the RWM has been used to generate economic block truncation coding for real-time compression [9]. Then, a color quantization technique was introduced to design a feasible color palette based on RWM [10].…”

Section: A Review Of the Rwm And Iwtmentioning

confidence: 99%

High-Payload Digital Watermarking Using Radius-Weighted Mean Based on IWT Domain

Yang

2013

2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing

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Based on integer wavelet transform (IWT), the author uses the idea of radius-weighted mean (RWM) and present a high-capacity color image watermarking scheme. More specifically, the Euclidean distance of RWM and centroid is used as the embedding criterion, a watermark is hidden in the low-low (LL) subbnad of IWT domain. To further promote payload size, the criterion of Euclidean norm of RWM is employed in the low-high (LH) and high-low (HL) subbnads of IWT domain. Simulations confirm that the marked images generated by the proposed method are robust against manipulations such as JPEG, JPEG2000, color quantization, cropping, (edge) sharpening, noise additions, blurring, and inversion. In addition, the resultant perceived quality is good while our peak signal-to-noise ratio outperforms existing techniques.

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“…where MN is the size of the image. The RWM is a special type of point (also known as a shape-specific point), originally introduced to register shapes [12], [13] and has thereafter been used to generate economic block truncation coding for real-time compression [14]. The RWM was subsequently used for color image quantization to generate a feasible palette [15].…”

Section: Review Of Rwmmentioning

confidence: 99%

Robust Watermarking Scheme Based on Radius Weight Mean and Feature-Embedding Technique

Yang¹

2013

ETRI J

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In this paper, the radius weight mean (RWM) and the feature-embedding technique are used to present a novel watermarking scheme for color images. Simulations validate that the stego-images generated by the proposed scheme are robust against most common image-processing operations, such as compression, color quantization, bit truncation, noise addition, cropping, blurring, mosaicking, zigzagging, inversion, (edge) sharpening, and so on. The proposed method possesses outstanding performance in resisting high compression ratio attacks: JPEG2000 and JPEG. Further, to provide extra hiding storage, a steganographic method using the RWM with the least significant bit substitution technique is suggested. Experiment results indicate that the resulting perceived quality is desirable, whereas the peak signal-to-noise ratio is high. The payload generated using the proposed method is also superior to that generated by existing approaches.

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EBTC: An economical method for searching the threshold of BTC compression

Cited by 7 publications

References 4 publications

Fuzzy block truncation coding

Fuzzy block truncation coding

High-Payload Digital Watermarking Using Radius-Weighted Mean Based on IWT Domain

Robust Watermarking Scheme Based on Radius Weight Mean and Feature-Embedding Technique

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