Real-time lossless compression of microarray images by separate compaction of foreground and background

Microarray technology is a powerful tool in molecular biology which is used for concurrent monitoring of large number of genes expressions. Each microarray experiment produces hundreds of images. Each digital image requires a large storage space. Hence, real-time processing of these images and transmission of them necessitates efficient and custom-made lossless compression schemes. In this paper, we present a hardware scheme for lossless compression scheme of 16-bit microarray images. The most significant part of the image pixels are compressed by classifying them into foreground and background regions. The foreground regions are packed together using a novel compaction unit. Same is performed for the background part. It is shown that a prediction process and a subsequent entropy coding of the packed pixels result in lower entropy. The segmentation map is also compressed with the same proposed compaction unit. The least significant part of the pixels is transmitted without compression. Real-time compression of these images is achieved while the bit-per-pixel values are comparable with the standard offline compression tools.