Hadamard Transform Image Coding for Bit Rate Control
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Solution Overview
Problem
Existing image coding apparatuses face challenges in accurately selecting coding conditions due to the limitations of using activity as a complexity parameter, leading to potential bit rate discrepancies and degraded image quality.
Innovation Solution
An image coding apparatus that employs a Hadamard transform unit to calculate a characteristic value for each picture, which includes frequency components, allowing for precise determination of quantization parameters and scene changes, thereby improving code amount control and image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If activity is used as a characteristic value indicating image complexity, then the code amount control process can be performed, but the selection of appropriate coding conditions becomes inaccurate leading to bit rate discrepancies and degraded image quality
Solution Approach 1:
The patent changes the parameter used for measuring image complexity from activity (spatial domain) to Hadamard transform coefficients (frequency domain). Specifically, it uses the sum of absolute values of AC components from Hadamard transform, which provides a more accurate representation of image complexity by capturing frequency characteristics. This parameter change resolves the contradiction by enabling both precise complexity measurement and reliable coding condition selection.
2Productivity
If activity-based complexity measurement is used, then code amount control can be performed, but the bit rate of coded image data may be largely different from the target bit rate
Solution Approach 1:
The patent transitions from using activity-based parameters to Hadamard transform-based parameters for complexity measurement. The Hadamard transform decomposes the image into frequency components, and the sum of absolute AC components provides a more precise measure of actual image complexity. This enables more accurate prediction of code amount and better control to achieve the target bit rate, resolving the contradiction between control efficiency and bit rate accuracy.
3Productivity
If activity is used to determine coding conditions, then the coding process can proceed, but image quality may be degraded due to inappropriate quantization parameter selection
Solution Approach 1:
The patent changes the basis for determining quantization parameters from activity values to Hadamard transform coefficients. By using the sum of absolute AC components from Hadamard transform, the system achieves more accurate complexity assessment, which leads to more appropriate quantization parameter selection. This resolves the contradiction by maintaining fast coding process speed while improving image quality through better-adapted quantization parameters.
Data Source
AI summary
In an image coding apparatus (1), a Hadamard transform unit (11) performs horizontal Hadamard transform on a picture of uncompressed image data (21). The sum total of absolute values of AC component values obtained by the Hadamard transform is calculated as a Hadamard value (23) of the picture. A scene change determination unit (12) determines whether a scene change occurs or not in the picture on the basis of the Hadamard value (23). In a case where a scene change occurs in the picture or where a differential absolute value between the amount of generated codes in a coded GOP and the ideal amount of codes in a GOP is larger than a predetermined reference value, a quantization parameter determination unit (13) determines a quantization parameter (24) of the picture on the basis of the Hadamard value (23) and the target amount of codes of the picture. A coding unit (14) codes the picture by using the determined quantization parameter (24).