My research interests include image and data compression, video codecs, sensor network and low-powered microcontrollers.

Data compression is a challenging process with important practical applications. Specialized techniques for lossy and lossless data compression have been the subject of numerous investigations during last several decades. The purpose of a data compression process is to reduce the file size while minimizing the deterioration of information on the data. Reducing redundant data in a file is one of the common approaches used by most compression algorithms. There are two main types in data compression: lossy and lossless. In lossy compression, some information of the data may be ignored in encoding. When the encoded data is decoded, the original file and the decompressed file may differ. When portions of the data are not completely essential and minor loss in data is acceptable, lossy compression algorithms may be preferred in order to maximize compression gain. In lossless compression, while the quality of a file is preserved, the reduction in the file size may not be as good as in lossy compression.

Lossless compression of images

Color-mapped images

Pseudo-distance Transform (PDT) is used in lossless compression of color-mapped images. PDT uses neighboring pixels to create a pseudo-distance table and transforms index values into pseudo-distance table values, as shown below.