Deep image compression with lifting scheme: Wavelet transform domain based on high‐frequency subband prediction

The multi-resolution watermarking method for digital images proposed in this work. The multiscale ridgelet coefficients of low and high frequency bands of the watermark is embedded to the most significant coefficients at low and high frequency bands of the multiscale ridgelet of an host image, respectively. A multi-resolution nature of multiscale ridgelet transform is exploiting in the process of edge detection. Experimental results of the proposed watermarking method are compared with the previously available watermarking algorithm wavelet transform. Moreover, the proposed watermarking method also tested on images attached by Discrete Cosine Transform (DCT) and wavelet based lossy image compression techniques.

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Research of Image Compression Based on Fractal Coding

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.241-244.418 ◽

2012 ◽

Vol 241-244 ◽

pp. 418-422

Author(s):

Dong Mei Wang ◽

Jing Yi Lu

Keyword(s):

Wavelet Transform ◽

Theoretical Analysis ◽

Image Compression ◽

High Frequency ◽

Wavelet Transformation ◽

Simulation Experiment ◽

Low Frequency ◽

Reconstructed Image ◽

Wavelet Domain ◽

Fractal Coding

The EZW and Fractal Coding were researched and simulated in this paper. And two drawbacks were discovered in these algorithm:the coding time is too long and the effect of reconstructed image is not ideal. Therefore, The paper studied the wavelet transformation in the fractal coding application, The wavelet coefficients of an image present two characteristics when the image is processed by wavelet transform: first characteristic is that the energy of an image is strongly concentrated in low frequency sub-image, second characteristic is that there is a similarity between the same direction in high frequency sub-images.but the fractal coding essence was precisely uses the similarity of wavelet transform image. The paper designed one kind of new Image Compression based on Fractal Coding in wavelet domain. The theoretical analysis and the simulation experiment indicated that, to some extent the method can reduce the coding time and reduce the MSE and enhance compression ratio of the reconstructed image and improve PSNR of the reconstructed image..

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Multiresolution Analysis of Fractal Image Compression

Fractals ◽

10.1142/s0218348x97000772 ◽

1997 ◽

Vol 05 (supp01) ◽

pp. 215-229

Author(s):

Gregory Caso ◽

C.-C. Jay Kuo

Keyword(s):

Wavelet Transform ◽

Image Compression ◽

Domain Structure ◽

Multiresolution Analysis ◽

Transform Coding ◽

Transform Domain ◽

Fractal Image Compression ◽

Fractal Image ◽

Affine Mappings ◽

Encoding Method

In this research, we perform a multiresolution analysis of the mappings used in fractal image compression. We derive the transform-domain structure of the mappings and demonstrate a close connection between fractal image compression and wavelet transform coding using the Haar basis. We show that under certain conditions, the mappings correspond to a hierarchy of affine mappings between the subbands of the transformed image. Our analysis provides new insights into the mechanism underlying fractal image compression, leads to a new non-iterative transform-domain decoding algorithm, and suggests a new transform-domain encoding method with extensions to wavelets other than the Haar transform.

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