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Shenda Li

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Proceedings Article | 10 April 2018 Paper

Adaptive bit plane quadtree-based block truncation coding for image compression

Shenda Li, Jin Wang, Qing Zhu

Proceedings Volume 10615, 106151K (2018) https://doi.org/10.1117/12.2302935

KEYWORDS: Quantization, Image compression, Image quality, Image processing, Edge detection, Image segmentation, Visualization

Read Abstract +

Block truncation coding (BTC) is a fast image compression technique applied in spatial domain. Traditional BTC and its variants mainly focus on reducing computational complexity for low bit rate compression, at the cost of lower quality of decoded images, especially for images with rich texture. To solve this problem, in this paper, a quadtree-based block truncation coding algorithm combined with adaptive bit plane transmission is proposed. First, the direction of edge in each block is detected using Sobel operator. For the block with minimal size, adaptive bit plane is utilized to optimize the BTC, which depends on its MSE loss encoded by absolute moment block truncation coding (AMBTC). Extensive experimental results show that our method gains 0.85 dB PSNR on average compare to some other state-of-the-art BTC variants. So it is desirable for real time image compression applications.

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