Pixel Index Encoding for High-Resolution Image Compression
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Solution Overview
Problem
Existing image compression methods for electronic apparatuses face challenges in efficiently using limited hardware resources while maintaining a constant compression rate and minimizing loss of image quality, especially for high-resolution images.
Innovation Solution
An electronic apparatus and method that encodes images by considering chrominance and luminance signals of pixels, selecting similar neighboring pixels, and replacing pixel values with index information to achieve high compression rates with minimal loss of image quality, using a processor to identify and store index information for pixel combinations based on similarity thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If lossless image compression is used to minimize loss of image quality, then image quality is preserved, but compression rate is not constant and hardware resources are not efficiently used
Solution Approach 1:
The patent transforms the image compression approach by changing parameters from storing full pixel values to storing only index information that references pixel combinations. This parameter change enables constant compression rates while maintaining image quality through selective reconstruction of pixel values based on similarity thresholds.
Solution Approach 2:
The patent creates simplified copies of pixel information by representing pixels as indices pointing to combinations of neighboring pixels. Instead of storing complete pixel data, the system stores references to reconstructed pixel combinations, reducing storage requirements while preserving visual fidelity.
2Manufacturing precision
If high-resolution images are processed to improve image quality, then image fidelity increases, but memory capacity and bandwidth requirements increase geometrically
Solution Approach 1:
The patent segments pixel information into two distinct components: index information (stored in the encoded image) and reference pixel combinations (stored separately). This segmentation allows the system to process high-resolution images by storing only compact index references rather than complete pixel data, dramatically reducing memory capacity requirements.
Solution Approach 2:
The patent introduces a new dimensional approach by separating storage of index information from storage of actual pixel values. This dimensional change allows the system to handle high-resolution images efficiently by storing minimal index data that can be expanded back to full resolution when needed, rather than storing all pixel data at full resolution continuously.
3Productivity
If pixel values are replaced with index information to increase compression rate, then storage efficiency improves, but image quality may be degraded
Solution Approach 1:
The patent implements a feedback mechanism through similarity threshold evaluation. The system evaluates whether replacing a pixel with an index reference maintains acceptable image quality by comparing the original pixel against reconstructed pixel combinations. This feedback loop ensures that compression is applied only when quality degradation remains within acceptable limits, balancing compression rate with image quality preservation.
Data Source
AI summary
An electronic apparatus includes: a storage and a processor. The processor is configured to: select a second pixel having a similarity to a first pixel equal to or greater than a threshold value among neighboring pixels based on a first chrominance signal of the first pixel and second chrominance signals of pixels neighboring the first pixel among a plurality of pixels included in an input image, identify index information corresponding to a pixel combination having a highest similarity to the first pixel based on a first luminance signal of the first pixel, a second luminance signal of the second pixel, and a plurality of pixel combinations with respect to the first pixel, and control the electronic apparatus to store the image by replacing a pixel value of the first pixel with the identified index information.