Adaptive Image Encoding for Fixed-Length Edge-Preserving Compression
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Solution Overview
Problem
Conventional image encoding methods face challenges in maintaining fixed encoding length while minimizing image degradation, especially at image edges, due to varying differential values, leading to increased bit requirements and reduced compression rates.
Innovation Solution
The image encoding device automatically selects between PCM and DPCM processing based on differential values, adjusting quantization steps according to threshold values, to encode pixels with large or small differential values effectively, ensuring fixed-length encoding and minimizing image degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If DPCM encoding is applied to image data with large differential values (e.g., at edges), then fixed-length encoding is achieved, but image degradation increases
Solution Approach 1:
The patent applies different encoding methods to different regions of the image based on local characteristics. Specifically, it uses DPCM encoding for regions with small differential values and PCM encoding for regions with large differential values (such as edges), thereby adapting the encoding quality to the local image content and preventing degradation at critical areas
Solution Approach 2:
The patent dynamically adjusts the encoding method for each pixel based on the differential value between adjacent pixels. By calculating the differential value and comparing it against a threshold, the system selectively applies DPCM or PCM encoding on a per-pixel basis, making the encoding process adaptive rather than static
2Manufacturing precision
If encoding bits are increased to prevent image degradation at edges, then image quality improves, but compression rate decreases
Solution Approach 1:
The patent applies different encoding methods to different regions of the image based on local characteristics. Specifically, it uses DPCM encoding for regions with small differential values and PCM encoding for regions with large differential values (such as edges), thereby adapting the encoding quality to the local image content and preventing degradation at critical areas
Solution Approach 2:
The patent changes the encoding parameter (encoding method) based on the differential value parameter. By setting a threshold for the differential value and switching between DPCM and PCM methods accordingly, the system optimizes the balance between image quality and compression rate by using more bits only where necessary
3Manufacturing precision
If PCM encoding is used for all pixels, then image quality is maintained, but data amount increases
Solution Approach 1:
The patent applies different encoding methods to different regions of the image based on local characteristics. Specifically, it uses DPCM encoding for regions with small differential values and PCM encoding for regions with large differential values (such as edges), thereby adapting the encoding quality to the local image content and preventing degradation at critical areas
Solution Approach 2:
The patent changes the encoding parameter (encoding method) based on the differential value parameter. By setting a threshold for the differential value and switching between DPCM and PCM methods accordingly, the system optimizes the balance between image quality and compression rate by using more bits only where necessary
Data Source
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AI summary
An image encoding device comprises: a predicted value generation means for predicting target pixel data which is the pixel data of an encoding target pixel to generate predicted value data; a subtractor for calculating the difference value between the target pixel data and the predicted value data to generate difference value data; an encoding mode decision means for determining an encoding mode based on the difference value data and temporarily holding it in a buffer; an encoding target decision means for determining which data of the target pixel or the difference value is used as encoding target data to be encoded based on the encoding mode; a quantization means for applying a quantization processing to the encoding target data based on the encoding mode to generate quantized data; and a fixed-length code generation means for adding the encoding mode to the quantized data to generate a fixed-length code.