|M.Sc Student||Kisler Rachel|
|Subject||Spatial-Spectral Sampling Technique for Color Images|
|Department||Department of Electrical Engineering||Supervisors||Professor Ron Kimmel|
|Professor Ron Meir|
The number of bits it takes
to represent an image is important in
storage and transmission. Color quantization, which was an active
research field in the last two decades, is one way to reduce the
memory requirements for images display and transmission. Reducing the image
resolution, or using different image sampling techniques are
alternative procedures that are used for image compression.
Our goal is to present a new non-uniform irregular image sampling technique, based on a combination of color (spectral) and resampling (spatial) quantization. We present an algorithm that extends existing sampling techniques for gray level images to color and video sequences. The result of the algorithm is dense sampling along the edges and sparse uniform samples in homogeneous domains. The algorithm explores the relation between the spectral and spatial information to achieve efficient image compression at low bitrate. We compare the results to other irregular sampling schemes and the JPEG algorithm.