Memory-efficient architecture of 2-D lifting-based discrete wavelet transform

Hsia, Chih-Hsien; Li, Weiming; Chiang, Jen‐Shiun

doi:10.1080/02533839.2011.577601

Cited by 5 publications

(1 citation statement)

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“…The 1-D DWT can be implemented by the lifting structure (Daubechies & Sweldens, 1998;Hsia, Li, & Chiang, 2011). This type of lifting structure works well in presenting horizontal and vertical edges (Sweldens, 1996), but fails to provide an efficient representation for directional areas, such as edges, and these edges may be neither horizontal nor vertical.…”

Section: Introductionmentioning

confidence: 99%

Edge-preserving image compression using adaptive lifting wavelet transform

Zhang

Qiu

2014

International Journal of Electronics

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In this paper, a novel 2-D adaptive lifting wavelet transform is presented. The proposed algorithm is designed to further reduce the high-frequency energy of wavelet transform, improve the image compression efficiency and preserve the edge or texture of original images more effectively. In this paper, a new optional direction set, covering the surrounding integer pixels and sub-pixels, is designed. Hence, our algorithm adapts far better to the image orientation features in local image blocks. To obtain the computationally efficient and coding performance, the complete processes of 2-D adaptive lifting wavelet transform is introduced and implemented. Compared with the traditional lifting-based wavelet transform, the adaptive directional lifting and the direction-adaptive discrete wavelet transform, the new structure reduces the highfrequency wavelet coefficients more effectively, and the texture structures of the reconstructed images are more refined and clear than that of the other methods. The peak signal-to-noise ratio and the subjective quality of the reconstructed images are significantly improved.

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Section: Introductionmentioning

confidence: 99%