Khire Sourabh, Cooper Lee, Park Yuna, Carter Alexis, Jayant Nikil, Saltz Joel
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:5424-7. doi: 10.1109/EMBC.2012.6347221.
Modern imaging technology permits obtaining images at varying depths along the thickness, or the Z-axis of the sample being imaged. A stack of multiple such images is called a Z-stack image. The focus capability offered by Z-stack images is critical for many digital pathology applications. A single Z-stack image may result in several hundred gigabytes of data, and needs to be compressed for archival and distribution purposes. Currently, the existing methods for compression of Z-stack images such as JPEG and JPEG 2000 compress each focal plane independently, and do not take advantage of the Z-signal redundancy. It is possible to achieve additional compression efficiency over the existing methods, by exploiting the high Z-signal correlation during image compression. In this paper, we propose a novel algorithm for compression of Z-stack images, which we term as ZPEG. ZPEG extends the popular discrete-cosine transform (DCT) based image encoder to compress Z-stack images. This is achieved by decorrelating the neighboring layers of the Z-stack image using differential pulse-code modulation (DPCM). PSNR measurements, as well as subjective evaluations by experts indicate that ZPEG can encode Z-stack images at a higher quality as compared to JPEG, JPEG 2000 and JP3D at compression ratios below 50∶1.
