We present a lossless and low-complexity image compression algorithm for endoscopic images. The algorithm consists of a static prediction scheme and a combination of golomb-rice and unary encoding. It does not require any buffer memory and is suitable to work with any commercial low-power image sensors that output image pixels in raster-scan fashion. The proposed lossless algorithm has compression ratio of approximately 73% for endoscopic images. Compared to the existing lossless compression standard such as JPEG-LS, the proposed scheme has better compression ratio, lower computational complexity, and lesser memory requirement. The algorithm is implemented in a 0.18？μm CMOS technology and consumes 0.16？mm × 0.16？mm silicon area and 18？μW of power when working at 2 frames per second. 1. Introduction Wireless capsule endoscopy (WCE) [1–4] is a state-of-the-art technology to receive images of human intestine for medical diagnostics. In this technique, the patient ingests a specially designed electronic capsule which has imaging and wireless circuitry embedded inside (as shown in Figure 1). While the capsule travels through the gastrointestinal (GI) tract, it captures images and sends them wirelessly to an outside workstation (i.e., PC), where the images are reconstructed and displayed on a monitor for medical diagnostics. The development of wireless capsule endoscopy has changed video endoscopy of the little intestine into a much invasive and more complete examination. The increasing use of these resources and the comfort and ease with which some of these examinations can be performed makes it likely that wireless capsule video imaging will have a substantial impact on the management of small intestinal disease as well as other parts of the body. The capsule runs on button batteries that need to supply power for about 8–10 hours . In this paper, our focus is on the image compressor in the capsule. Here, we propose an image compression algorithm by exploring the unique properties of endoscopic images. The scheme consists of a simple and static prediction scheme and encoding the error both in golomb-rice [5, 6] and in unary coding. The algorithm is particularly suitable to work with any commercial low-power image sensors [7, 8] that output image pixels in raster scan fashion, eliminating the need of large buffer memory to store the complete image frame. The proposed algorithm has low computational complexity and it is simple to implement. Figure 1: Block diagram of an endoscopic capsule. There have been some works reported on the image compressor of the
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