The main challenge in video capsule endoscopic system is to reduce the area and power consumption while maintaining acceptable video reconstruction. In this paper, a subsample-based data compressor for video endoscopy application is presented. The algorithm is developed around the special features of endoscopic images that consists of a differential pulse-coded modulation (DPCM) followed by Golomb-Rice coding. Based on the nature of endoscopic images, several subsampling schemes on the chrominance components are applied. This video compressor is designed in a way to work with any commercial low-power image sensors that outputs image pixels in a raster scan fashion, eliminating the need of memory buffer and temporary storage (as needed in transform coding schemes). An image corner clipping algorithm is also introduced. The reconstructed images have been verified by five medical doctors for acceptability. The proposed low-complexity design is implemented in a 0.18 μm CMOS technology and consumes 592 standard cells, 0.16 × 0.16 mm silicon area, and 42 μW of power. Compared to other algorithms targeted to video capsule endoscopy, the proposed raster-scan-based scheme performs strongly with a compression ratio of 80% and a very high reconstruction peak signal-to-noise ratio (over 48 dB).