An efficient image compression technique using Tchebichef bit allocation

Ernawan, Ferda; Kabir, Muhammad Nomani; Zamli, Kamal Z.

doi:10.1016/j.ijleo.2017.08.007

Cited by 41 publications

(15 citation statements)

References 24 publications

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“…Using the experiment, we find a threshold as an optimal trade-off between transparency and robustness against JPEG compression for the proposed scheme. JPEG compression is the most popular standard image compression techniques and it has been widely implemented on most digital cameras [27]- [37]. The experimental results have revealed the optimal thresholds as about 0.016 and 0.24 for luminance and chrominance, respectively as shown in Figure 2.…”

Section: Resultsmentioning

confidence: 98%

A Blind Multiple Watermarks based on Human Visual Characteristics

Ernawan¹,

Liew²,

Mustaffa³

et al. 2018

IJECE

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Digital watermarking is an alternative solution to prevent unauthorized duplication, distribution and breach of ownership right. This paper proposes a watermarking scheme for multiple watermarks embedding. The embedding of multiple watermarks use a block-based scheme based on human visual characteristics. A threshold is used to determine the watermark values by modifying first column of the orthogonal U matrix obtained from Singular Value Decomposition (SVD). The tradeoff between normalize cross-correlation and imperceptibility of watermarked image from quantization steps was used to achieve an optimal threshold value. The results show that our proposed multiple watermarks scheme exhibit robustness against signal processing attacks. The proposed scheme demonstrates that the watermark recovery from chrominance blue was resistant against different types of attacks.

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Section: Resultsmentioning

confidence: 98%

A Blind Multiple Watermarks based on Human Visual Characteristics

Ernawan¹,

Liew²,

Mustaffa³

et al. 2018

IJECE

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“…, N −1 and f (x, y) denotes the intensity value at the pixel position (x, y) in the image. The term t n (x) is defined using the following recursive relation [23]:…”

Section: A Arnold Transformmentioning

confidence: 99%

An Improved Watermarking Technique for Copyright Protection Based on Tchebichef Moments

Ernawan

Kabir

2019

IEEE Access

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Watermarking technique is a method to protect ownership of digital multimedia. Most existing watermarking techniques achieve a good level of imperceptibility and robustness. The challenges to achieve higher invisibility and resistance with lower computational time motivate researchers to work on new watermarking schemes. Robustness against noise attacks and JPEG2000 compression needs to be improved to acquire a better resistance capability of the watermark. In this paper, we present a block-based Tchebichef watermarking technique for protecting copyrights. In this technique, the host image is first divided into non-overlapping blocks and Tchebichef moments are calculated for each block. The watermarks are embedded into the blocks with lower visual entropies. The watermark image is scrambled by Arnold transform before embedding into the Tchebichef moments of the selected image blocks. The proposed watermarking scheme was tested under noise additions, filtering, cropping and compressing attacks. Our scheme was verified and compared to the existing watermarking techniques under image geometric and processing attacks. Furthermore, the proposed scheme demonstrated a superior performance in robustness under noise attacks and JPEG2000. INDEX TERMS Watermarking, copyright protection, embedding algorithm, tchebichef moments, visual entropies.

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“…The discrete orthogonal moments (DOMs) are widely applied in various fields of signal and image analysis. Applications of DOMs include signal and image reconstruction [8,9,50], image classification [3,16,20,39], face recognition [33], image watermarking [24,41,44], signal zero-watermarking [10], edge detection [35], image encryption [43], signal compression [11,2] and image compression [13,42]. The computation of DOMs involves the computation of kernel discrete orthogonal polynomials (DOPs) such as Tchebichef [27,28], Krawtchouk [45,47], Hahn [46,50], Meixner [12,21], Charlier [8,19,34], dual Hahn [20,48], Racah [49] and Shmaliy [26] polynomials.…”

Section: Introductionmentioning

confidence: 99%

Fast and stable computation of higher-order Hahn polynomials and Hahn moment invariants for signal and image analysis

Daoui

Karmouni

Sayyouri

et al. 2021

Multimed Tools Appl

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This article presents, on the one hand, new algorithms for the fast and stable computation of discrete orthogonal Hahn polynomials of high order (HPs) based on the elimination of all gamma and factorial functions that cause the numerical fluctuations of HPs, and based on the use of appropriate stability conditions. On the other hand, a new method for the fast and numerically stable computation of Hahn moment invariants (HMIs) is also proposed. This method is mainly based on the use of new recursive relations of HPs and of matrix multiplications when calculating HMIs. To validate the efficiency of the algorithms proposed for the calculation of HPs, several signals and large images (≥4000 × 4000) are reconstructed by Hahn moments (HMs) up to the last order with a reconstruction error tending towards zero ( MSE ≃ 10 −10 ). The efficiency of the proposed method for calculating HMIs is demonstrated on large medical images (2048 × 2048) with a very low relative error ( RE ≃ 10 −10 ). Finally, comparisons with some recent work in the literature are provided.

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An efficient image compression technique using Tchebichef bit allocation

Cited by 41 publications

References 24 publications

A Blind Multiple Watermarks based on Human Visual Characteristics

A Blind Multiple Watermarks based on Human Visual Characteristics

An Improved Watermarking Technique for Copyright Protection Based on Tchebichef Moments

Fast and stable computation of higher-order Hahn polynomials and Hahn moment invariants for signal and image analysis

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