Abstract
In order to decrease the communication bandwidth and save the transmitting power in the wireless endoscopy capsule, this paper presents a new near-lossless image compression algorithm based on the Bayer format image suitable for hardware design. This algorithm can provide low average compression rate (2.12 bits/pixel) with high image quality (larger than 53.11 dB) for endoscopic images. Especially, it has low complexity hardware overhead (only two line buffers) and supports real-time compressing. In addition, the algorithm can provide lossless compression for the region of interest (ROI) and high-quality compression for other regions. The ROI can be selected arbitrarily by varying ROI parameters. In addition, the VLSI architecture of this compression algorithm is also given out. Its hardware design has been implemented in 0.18 µm CMOS process.
Highlights
Compared to the conventional endoscopy system, the wireless capsule endoscopy allows us to directly study the entire small intestine and does not require any sedation, anesthesia, or insufflation of the bowel
This paper presents a new near-lossless image compression algorithm for the wireless endoscopy system
A low-complexity and highly efficient image compression algorithm suitable for ASIC design based on the Bayer format image applied in wireless endoscopy system has been presented
Summary
Compared to the conventional endoscopy system, the wireless capsule endoscopy allows us to directly study the entire small intestine and does not require any sedation, anesthesia, or insufflation of the bowel. A new low-complexity and high-quality image compression for digital image sensor with Bayer color filter arrays needs to be used [2]. [8] presents a new lossless compression based on wavelet transformation, its computation complexity is so high for wireless endoscopy application. This paper presents a new near-lossless image compression algorithm for the wireless endoscopy system. It has low complexity hardware implementation and supports real-time compressing. PSNR larger than 46.37 dB and no more than 2 intensity levels error for a pixel is defined as near-lossless This strict definition assures high image quality, which is safe for patient diagnosis.
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