Multimedia Image Compression Method Based on Biorthogonal Wavelet and Edge Intelligent Analysis

Liu, Tao; Wu, Ying

doi:10.1109/access.2020.2984263

Cited by 7 publications

(2 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, DCT does not have the multiresolution transform property. In all these respects, DWT is superior [33]. With DWT, one can obtain the resulting filtered image after going through various levels of discrete wavelet decomposition.…”

Section: Fundamental Conceptsmentioning

confidence: 99%

An Improved Image Compression Algorithm Using 2D DWT and PCA with Canonical Huffman Encoding

Ranjan,

Kumar

2023

Entropy

View full text Add to dashboard Cite

Of late, image compression has become crucial due to the rising need for faster encoding and decoding. To achieve this objective, the present study proposes the use of canonical Huffman coding (CHC) as an entropy coder, which entails a lower decoding time compared to binary Huffman codes. For image compression, discrete wavelet transform (DWT) and CHC with principal component analysis (PCA) were combined. The lossy method was introduced by using PCA, followed by DWT and CHC to enhance compression efficiency. By using DWT and CHC instead of PCA alone, the reconstructed images have a better peak signal-to-noise ratio (PSNR). In this study, we also developed a hybrid compression model combining the advantages of DWT, CHC and PCA. With the increasing use of image data, better image compression techniques are necessary for the efficient use of storage space. The proposed technique achieved up to 60% compression while maintaining high visual quality. This method also outperformed the currently available techniques in terms of both PSNR (in dB) and bit-per-pixel (bpp) scores. This approach was tested on various color images, including Peppers 512 × 512 × 3 and Couple 256 × 256 × 3, showing improvements by 17 dB and 22 dB, respectively, while reducing the bpp by 0.56 and 0.10, respectively. For grayscale images as well, i.e., Lena 512 × 512 and Boat 256 × 256, the proposed method showed improvements by 5 dB and 8 dB, respectively, with a decrease of 0.02 bpp in both cases.

show abstract

Section: Fundamental Conceptsmentioning

confidence: 99%

An Improved Image Compression Algorithm Using 2D DWT and PCA with Canonical Huffman Encoding

Ranjan,

Kumar

2023

Entropy

View full text Add to dashboard Cite

show abstract

“…The wavelet transform selects different spline functions to derive different wavelet bases, and uses finite-length attenuating wavelet base expansion and translation to perform multiscale refinement analysis on the signal. For signal nonstationary parts, only when the wavelet function does not coincide with it, the transform coefficient is not zero, which can remove the oscillation at the turning point, so it is suitable for the analysis of instantaneous nonstationary signals and overcomes the Gibbs effect [24]. Thus, it is suitable for the analysis of instantaneous nonstationary signals.…”

Section: Figure 4 the Gibbs Effectmentioning

confidence: 99%

Displacement Estimation of Self-Sensing Magnetic Bearings Based on Biorthogonal Spline Wavelet

et al. 2021

View full text Add to dashboard Cite

By collecting the ripple current in the control coil, the self-sensing magnetic bearings can obtain rotor displacement information without a displacement sensor, which has the advantages of low cost and high integration. According to the problems of incomplete and inaccurate displacement information extraction caused by the traditional displacement estimation method using Fourier method to analyze the ripple current with non-stationary characteristics to estimate the rotor displacement with the Gibbs effect. Therefore, this paper proposes a rotor displacement estimation algorithm based on multiresolution filter bank biorthogonal spline wavelet for a magnetic bearing motor based on two-level switching power amplifier. This algorithm utilizes the biorthogonal spline wavelet with the characteristics of generalized linear phase and tight support, which can accurately demodulate the ripple current in the coil and extract the displacement information in the ripple current. Therefore, it is able to overcome the Gibbs effect in the traditional Fourier analysis estimation algorithm, to reduce the influence of ripple on rotor displacement estimation, and to improve the accuracy and stability of displacement estimation. In order to verify the correctness and effectiveness of the proposed algorithm, this paper establishes a simulation model of magnetic bearing in MATLAB Simulink and designs the proposed displacement estimator. Simulation results demonstrate that the proposed algorithm has higher accuracy and better stability than traditional displacement estimation algorithms. Experimental results show that the maximum deviation rate of the displacement estimation method proposed in this paper does not exceed 1% when the radial magnetic bearing gap is 0.5 mm, which can effectively estimate the rotor displacement.

show abstract

Efficient and Flexible Compression of Very Sparse Networks of Big Data

Leung

Jiang

Zhang

2021

Lecture Notes in Social Networks

View full text Add to dashboard Cite

Multimedia Image Compression Method Based on Biorthogonal Wavelet and Edge Intelligent Analysis

Cited by 7 publications

References 43 publications

An Improved Image Compression Algorithm Using 2D DWT and PCA with Canonical Huffman Encoding

An Improved Image Compression Algorithm Using 2D DWT and PCA with Canonical Huffman Encoding

Displacement Estimation of Self-Sensing Magnetic Bearings Based on Biorthogonal Spline Wavelet

Efficient and Flexible Compression of Very Sparse Networks of Big Data

Contact Info

Product

Resources

About