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Fast downscaled inverses for images compressed with M-channel lapped transforms.
1Xerox Corp., Webster, NY.
Summary
This study introduces faster image decompression methods using partial decompression and reduced inverse transforms. These techniques simplify image recovery and reduce computational costs for various display resolutions.
Area of Science:
- Digital image processing
- Signal processing
- Computer vision
Background:
- Image decompression and display involve significant computational cost, especially when rescaling.
- Current methods for full decompression and spatial domain rescaling are resource-intensive.
Purpose of the Study:
- To investigate efficient image decompression techniques.
- To develop methods for faster image recovery and display at different resolutions.
- To simplify the image synthesis process.
Main Methods:
- Studied downscaled inverses involving partial decompression.
- Employed reduced inverse transforms for image recovery.
- Developed general solutions for M-channel finite impulse response (FIR) filterbanks.
- Designed faster inverses for block and lapped transforms.
Main Results:
- Partial decompression significantly reduces computational expense.
- Reduced inverse transforms simplify the image synthesis process.
- Faster inverse designs were achieved for common block and lapped transforms.
Conclusions:
- Downscaled inverses offer an efficient alternative to full decompression and rescaling.
- The proposed methods simplify image recovery and reduce processing costs.
- Efficient inverse transform designs are crucial for high-resolution image display.
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