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Proceedings Paper

Fast convolution on a programmable media processor and application in unsharp masking
Author(s): Ravi Managuli; Chris Basoglu; Sayan Dev Pathak; Yongmin Kim
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Paper Abstract

Convolution is a fundamental operation to many image processing algorithms and applications. One such algorithm is unsharp masking, which is widely used in medical imaging. A major component in unsharp masking is the computation of a lowpass-filtered image, e.g., via generalized convolution with a Gaussian filter or via specialized convolution with a boxcar filter. Generalized convolution is computationally expensive, e.g., convolution with a 3 X 3 kernel on a 512 X 512 image takes 1.45 sec on SUN SparcStation 20/71. In order to achieve faster computation in convolution, hardwired solutions with ASICs and/or fixed-function chips with little programmability have been traditionally used. The disadvantages associated with hardwired implementations are that they are rigid, uni-functional and not upgradable. Our approach has been programmable convolution, which is flexible, multi-functional, easily-upgradable and has a performance comparable to the hardwired implementations. This paper describes efficient software implementations of both generalized and boxcar convolution on a programmable multimedia processor, the Texas Instruments TMS320C80, also known as Multimedia Video Processor (MVP). Using the MVP's advanced digital signal processors (ADSPs), instruction-level parallelism and intelligent input/output interface, we have been able to significantly improve the performance of both generalized and boxcar convolution. For a 512 X 512 8-bit image, generalized convolution takes 19.5 ms for a 3 X 3 kernel. While the boxcar convolution has similar performance for a 3 X 3 kernel, the performance improvement by a factor of up to 13 has been achieved for large-size kernels such as 21 X 21. Our implementation of convolution algorithms on programmable mediaprocessor clearly demonstrates the feasibility of software-based approach.

Paper Details

Date Published: 26 June 1998
PDF: 11 pages
Proc. SPIE 3335, Medical Imaging 1998: Image Display, (26 June 1998); doi: 10.1117/12.312547
Show Author Affiliations
Ravi Managuli, Univ. of Washington (United States)
Chris Basoglu, Univ. of Washington (United States)
Sayan Dev Pathak, Univ. of Washington (United States)
Yongmin Kim, Univ. of Washington (United States)


Published in SPIE Proceedings Vol. 3335:
Medical Imaging 1998: Image Display
Yongmin Kim; Seong Ki Mun, Editor(s)

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