Geometric Image Transforms for Axis-Aligned DCT Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image compression methods result in lower compression ratios when compressing images with texture features that are not aligned with the image axis, leading to inefficient use of bits due to non-zero DCT coefficients.
Innovation Solution
Rotate or geometrically transform texture features in images to align them with the image axis before performing discrete cosine transform (DCT), generating mostly zero DCT coefficients for improved compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of moving object
If image compression is performed without aligning texture features, then the compression process is simple and fast, but the compression ratio is low due to non-zero DCT coefficients
Solution Approach 1:
The patent applies preliminary action by performing geometric transformation (rotation) on image blocks before conducting DCT compression. The system calculates the main direction within each block and rotates the block to align texture features with the horizontal/vertical directions before compression, thereby reducing non-zero DCT coefficients and improving compression ratio.
Solution Approach 2:
The patent changes the orientation parameter of image blocks through geometric transformation. By rotating blocks based on calculated main directions, the texture features are realigned to optimize the distribution of DCT coefficients, transforming the spatial orientation parameter to achieve better compression efficiency.
2Loss of substance
If geometric transformation is applied to align texture features, then compression ratio improves, but processing time and computational complexity increase
Solution Approach 1:
The patent segments the image into multiple blocks and processes each block independently. By dividing the image into smaller units, the geometric transformation and DCT operations can be performed on individual blocks, reducing the overall computational complexity and processing time compared to transforming the entire image at once.
Solution Approach 2:
The patent applies partial action by performing geometric transformation only on blocks where it is most beneficial. The system calculates the main direction for each block and applies rotation selectively, rather than uniformly transforming all blocks, thereby optimizing the balance between compression improvement and processing overhead.
Data Source
Figure 1A~1B
Figure 2A~2B
Figure 3A
AI summary
A decoder may perform a method of decompressing images that include texture features that are not aligned with an axis of the image being compressed. In some example implementation, the method may include receiving a block of geometrically transformed pixel values and performing an inverse geometric transformation on the block of geometrically transformed pixel values to generate a first block of pixel values. The geometrically transformed pixel values represent texture features of an image that are non-parallel with a vertical axis or a horizontal axis of the image and the first block of pixel values being one of a plurality of blocks of the image. The example method may further include generating at least a portion of the image based on the first block of pixel values.