Digital Image Resolution Conversion via Decimation and Interpolation
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Solution Overview
Problem
Existing methods for converting the resolution of digital images, such as decimation and interpolation, often result in image artifacts or are costly to implement, failing to provide a fast and efficient way to maintain high-quality image scaling.
Innovation Solution
A method that calculates the scale of conversion in both x and y directions, interpolates color values from nearest pixels, and uses a combination of decimation filters and replication to achieve efficient resolution conversion in digital color images, applicable to any color space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If simple decimation (throwing away data) is used, then implementation is easy and cost is low, but image quality deteriorates with unacceptable artifacts
Solution Approach 1:
The patent applies preliminary action by applying a decimation filter before the actual decimation process. The filter processes the input image in advance to smooth out pixels and reduce high-frequency components, which prevents the formation of unacceptable artifacts during subsequent decimation. This preliminary filtering action enables simple decimation to achieve acceptable image quality while maintaining implementation ease.
2Manufacturing precision
If decimation filter is used, then image quality improves with acceptable artifacts, but implementation cost and complexity increase
Solution Approach 1:
The patent segments the decimation process into two independent stages: a filtering stage that processes the input image to reduce high-frequency components, and a decimation stage that performs the actual pixel selection. This segmentation allows the complex filtering operation to be separated from the simple decimation operation, enabling the use of efficient algorithms like bit-reversal permutation for the decimation part while maintaining quality through the filtering part.
Solution Approach 2:
The patent uses copying by replicating pixel values during the enlargement process. When the image needs to be enlarged, the patent copies existing pixel values to generate new pixels, which is a simple and efficient operation that maintains image quality without requiring complex calculations. This copying approach is particularly effective for integer-scale enlargements.
3Manufacturing precision
If interpolation is used for enlargement, then image quality improves, but processing time and computational cost increase
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing lookup tables (LUTs) for interpolation operations. These LUTs contain pre-computed interpolation results for various pixel positions and color values, allowing the actual image enlargement to proceed much faster by simply table-lookup operations rather than performing complex interpolation calculations in real-time. This preliminary computation significantly boosts processing speed while maintaining interpolation quality.
4Productivity
If simple pixel replication is used for enlargement, then processing is fast and easy, but image quality deteriorates
Solution Approach 1:
The patent merges two operations: pixel replication for fast processing and interpolation for quality improvement. The system combines these by first applying interpolation to calculate intermediate pixel values, then using replication to efficiently generate the final enlarged image. This merging allows the system to benefit from both the speed of replication and the quality of interpolation, achieving both fast processing and good image quality.
Data Source
AI summary
Methods to convert the resolution of digital images have been achieved. The methods invented support the decrease or the increase of the resolution of digital images, even enlargement in one direction and decimation in the other direction. The methods invented are applicable for any color space used. In case of decimation the method invented combines an interpolation of source pixels to calculate the color values of the destination pixels and omitting some rows of source pixels. A linear interpolation method is used to get a fast result of the interpolation. In case of an enlargement of a digital image in one or two directions the method invented combines the calculation of the color values of the destination pixels by an interpolation of the nearest source pixels with an extrapolation of the destination pixels being close to the edge of the image according to the scale of the conversion of resolution in one or two directions.