Camera Module Pixel Group Compression for Multi-Resolution Storage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current image compression methods do not efficiently generate and utilize compressed data for images of multiple resolutions, leading to increased power consumption and storage inefficiencies in devices.
Innovation Solution
A camera module and image processing device that compresses image data by calculating representative pixel values and residual values, generating first and second compressed data streams, which are used to produce images of different resolutions, reducing data transmission and storage requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If current image compression methods are used to generate compressed data for multiple resolutions, then storage requirements increase and power consumption increases, but image quality and resolution flexibility are maintained
Solution Approach 1:
The image data is divided into multiple pixel groups, and compression is performed independently for each pixel group. This segmentation allows the system to generate compressed data for multiple resolutions simultaneously from a single compression process, eliminating the need for separate compression operations for each resolution and reducing overall storage requirements.
Solution Approach 2:
The compression method generates first compressed data that can be used to reconstruct images at multiple different resolutions (first resolution, second resolution, third resolution, etc.). This single compressed data set serves multiple functions and multiple resolution requirements, eliminating the need for separate compressed data sets for each resolution and significantly reducing storage requirements.
2Quantity of substance
If separate compressed data is generated for each resolution, then storage efficiency decreases, but resolution-specific optimization is achieved
Solution Approach 1:
The image is divided into multiple pixel groups that are processed independently during compression. This segmentation enables the compression algorithm to capture features at multiple scales simultaneously, allowing a single compressed data set to support multiple resolution requirements without requiring separate compression processes for each resolution.
Solution Approach 2:
The compression method uses representative pixel values calculated from multiple pixels in each pixel group, and generates compressed data that can be decoded at different resolution levels. By changing the decoding parameters rather than the compression parameters, the system can generate images at multiple resolutions from a single compressed data set, reducing data transmission requirements.
Data Source
AI summary
A camera module includes a compressor configured to divide a plurality of pixels included in image data, into a plurality of pixel groups, with respect to each of the plurality of pixel groups into which the plurality of pixels is divided, calculate a representative pixel value of a corresponding pixel group, based on pixel values of multiple pixels included in the corresponding pixel group, generate first compressed data, based on the calculated representative pixel value of each of the plurality of pixel groups, with respect to each of the plurality of pixel groups into which the plurality of pixels is divided, calculate residual values representing differences between the pixel values of the multiple pixels included in the corresponding pixel group and the representative pixel value of the corresponding pixel group, and generate second compressed data, based on the calculated residual values of each of the plurality of pixel groups.