Showing papers by "Russell M. Mersereau published in 1993"

Automatic detection of brain contours in MRI data sets

Abstract: A software procedure is presented for fully automated detection of brain contours from single-echo 3-D MRI data, developed initially for scans with coronal orientation. The procedure detects structures in a head data volume in a hierarchical fashion. Automatic detection starts with a histogram-based thresholding step, whenever necessary preceded by an image intensity correction procedure. This step is followed by a morphological procedure which refines the binary threshold mask images. Anatomical knowledge, essential for the discrimination between desired and undesired structures, is implemented in this step through a sequence of conventional and novel morphological operations, using 2-D and 3-D operations. A final step of the procedure performs overlap tests on candidate brain regions of interest in neighboring slice images to propagate coherent 2-D brain masks through the third dimension. Results are presented for test runs of the procedure on 23 coronal whole-brain data sets, and one sagittal whole-brain data set. Finally, the potential of the technique for generalization to other problems is discussed, as well as limitations of the technique. >

Motion compensated compression of computer animation frames

Abstract: This paper presents a new lossless compression algorithm for computer animation image sequences. The algorithm uses transformation information available in the animation script and floating point depth and object number information stored at each pixel to perform highly accurate motion prediction with very low computation. The geometric data, i.e., the depth and object number, is very efficiently compressed using motion prediction and a new technique called direction coding, typically to 1 to 2 bits per pixel. The geometric data is also useful in z-buffer image compositing and this new compression algorithm offers a very low storage overhead method for saving the information needed for zbuffer image compositing. The overall compression ratio of the new algorithm, including the geometric data overhead, is compared to conventional spatial linear prediction compression and is shown to be consistently better, by a factor of 1.4 or more, even with large frame-to-frame motion.

Vector quantization video encoder using hierarchical cache memory scheme

Abstract: A hierarchical encoding system (10) and method efficiently compress image blocks (21) by using various successive hierarchical stages (11-19) and motion encoders (13, 15, 17) which employ cache memories (36) updated by stack replacement algorithms. A background detector (11) initially compares the present image block (21) with a previous image block and if the present image block (21) is substantially similar to the previous image block, the background detector (11) terminates the encoding procedure by setting a first flag bit (32). Otherwise, the image block (21) is decomposed into smaller subblocks (21') in a quadtree structure. The smaller subblocks (21') are compared with previous image subblocks of comparable size within the present image block (21).

The symmetric convolution approach to the nonexpansive implementations of FIR filter banks for images

Abstract: The authors describe symmetric convolution and its use for the nonexpansive implementation of multirate filter banks for images. Symmetric convolution is a formalized approach to convolving symmetric FIR (finite impulse response) filters with symmetrically extended data. It is efficient because the discrete sine and cosine transforms can be used to perform the convolution as a transform-domain multiplication. The authors explain how to use symmetric convolution to implement a multiband filter bank for finite-length data that restricts the number of samples in the subbands but still gives perfect reconstruction. >

New approaches to block filtering of images using symmetric convolution and the DST or DCT

Abstract: New approaches to block filtering of images are presented based on the recently introduced operation of symmetric convolution. Symmetric convolution is a formalized approach to convolving symmetric finite impulse response (FIR) filters with symmetrically extended data. It is efficient because the discrete sine and cosine transforms (DST & DCT) can be used to perform the convolution as a transform-domain multiplication. With proper zero-padding of the input data, symmetric convolution gives the same result as linear convolution. As a consequence, it is now possible to use the overlap-add and overlap-save techniques with DSTs and DCTs in order to efficiently filter large images. An alternative method to conventional block filtering is proposed, whereby the blocks need not be overlapped. This approach is extended for those applications where reduced complexity is needed and the approximation to conventional linear filtering is adequate. >

Digital Filtering: A Computer Laboratory Textbook

Abstract: From the Publisher: Useful as a complement to a digital signal processing (DSP) text, as the text for an introductory laboratory course in DSP or as a self-paced introduction to DSP basics. Provides exposure to DSP in a computer environment. Includes a summary of the concepts basic to signal processing, nine projects and more than ten exercises to reinforce these concepts plus a library of DSP computer functions that run on personal computers using the MS-DOS operating system.

Efficient motion-oriented filter banks for video coding

Abstract: A new filter bank structure for subband coding of video is proposed. This filter bank is motion selective in a way that resembles the human visual system (HVS). The motion selectivity makes it well suited for motion compensation and for perception-based coding. The filter bank has a very efficient polyphase implementation. The effectiveness of these filter banks for motion separation is demonstrated. >

Contour-based hybrid displacement estimation for image sequence compression

Abstract: A contour-based hybrid scheme for video sequence displacement estimation is described. It is a combination of a contour-based and a multiframe gradient-based algorithm. By using three successive image frames, the proposed system can select reliable motion-related-frame differences, extract moving edge tokens, and ignore noise. The contour-based estimation method can provide a reasonable initial displacement estimate for each moving edge neighborhood. As only one motion vector per edge neighborhood needs to be transmitted and the receiver can find the edge and region information by itself, this approach can reduce the overhead bits to be transmitted. To complete a low-bit-rate video coding system, some coding algorithms need to be applied to transmit the motion-compensated frame differences. >