Presents the results of using the new MATLAB image processing toolbox and the C programming language in a senior-level image processing course at the University of Illinois. The course includes for the first time a formal lab component, so more time and effort have been devoted to computer algorithm implementation than previously. Students are expected to implement and test image processing algorithms in both MATLAB and C. The authors explore the benefits of using MATLAB and C to teach image processing, and evaluate the students' results in the lab.>

A multirate (MR) filter bank is called size-limited if the total number of output samples equals the number of input samples. A method called symmetric extension improved performance in subband image compression systems compared to the earlier method of circular convolution. However, the symmetric extension method was developed only for two-band uniform filter banks, and required even-length linear phase analysis filters. The authors generalize the symmetric extension method to the M-band, possibly nonuniform filter banks, where M=/>2. The length restriction on the analysis filters is relaxed.

In the above-titled paper (see ibid., vol. 2, p. 91-5, Mar. 1992), R. Rosenholtz and A. Zakhor proposed an effective method for reducing blocking in transform coded images. Their method uses two projection operators and the theory of projection onto convex sets (POCS) to guarantee convergence of the iteration. One projection operator is defined from the known quantization levels used to code the transform coefficients. The other projection is based on the set of bandlimited images with a given cutoff frequency. The algorithm they actually implemented is only tenuously related to the theory of POCS. A different basis for justifying their algorithm is offered, one that provides an exact formal basis for establishing convergence and a more flexible theory for elucidating the possibilities of the algorithm.>

Current work in combining multirate filtering techniques with a three-source (low pass, edge, and texture) image model designed to increase control over perceptual edge quality is described. The model employs multirate subband filtering to code the low-pass source efficiently and to reconstruct the image from the sources. Spline modeling can be used to exploit the two-dimensional connectivity of the edge source. Parameters of the edge profile (edge-source values along the perpendicular direction) are chosen so that coding errors are not too perceptually objectionable. Using a two-level octave band frequency configuration and without coding the sources, the SNR is 57.0 dB, perceptually indistinguishable from the original.>

The extension of one-dimensional subband coding techniques to two-dimensional image processing has recently been shown to be highly effective for image compression. Straightforward extension of the QMF analysis/synthesis system, however, increases the region of support of the output image, an undesirable result for data reduction applications. Circular convolution has been used as a way to limit the region of support. A new system is introduced, the symmetric extension method, which also limits the region of support. This paper shows that the symmetric extension method outperforms the circular convolution method in the presence of coding noise.