Video Decoding with Scaled DC Coefficients for Block Restoration
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Solution Overview
Problem
Existing video codecs struggle with effectively encoding and decoding high-resolution or high-quality video content due to limitations in block-based encoding methods, leading to inefficiencies in data compression and image restoration.
Innovation Solution
The proposed method involves selecting a current block and determining multiple transform blocks, scaling direct current (DC) transform coefficients based on block sizes, and performing inverse transforms to improve image decoding and encoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If block-based encoding methods are used for video compression, then data compression efficiency is improved, but image restoration quality deteriorates
Solution Approach 1:
The image is divided into multiple blocks of different sizes, and each block is processed independently with appropriate transform coefficients. This segmentation allows the encoding method to adapt to local image characteristics while maintaining overall compression efficiency, resolving the contradiction between compression efficiency and restoration quality.
Solution Approach 2:
Different transform coefficients (DC and AC) are applied to different blocks based on their local characteristics. The DC coefficient handles the average intensity of each block while AC coefficients capture local variations. This local quality approach ensures that each block is restored with appropriate detail, improving overall image restoration quality without sacrificing compression efficiency.
2Manufacturing precision
If high-resolution video content is encoded using traditional methods, then image quality is maintained, but computational complexity increases
Solution Approach 1:
The high-resolution image is segmented into multiple smaller blocks, allowing parallel processing and reducing the computational burden on each processing unit. This segmentation maintains image quality by preserving local details while enabling efficient computation through distributed processing.
Solution Approach 2:
The method transforms image data from spatial domain to frequency domain using transform coefficients, changing the representation parameters to enable more efficient compression and processing. This parameter transformation maintains image quality while reducing computational complexity for encoding and decoding operations.
3Quantity of substance
If transform coefficients are used for compression, then data reduction is achieved, but compression efficiency is limited
Solution Approach 1:
The patent applies different transform coefficients (DC and AC) to different blocks based on local image characteristics. This local quality approach enables more effective data reduction by allocating transform coefficients according to local variance, achieving better compression efficiency while maintaining image quality.
Solution Approach 2:
The encoding method dynamically selects and applies appropriate transform coefficients for each block based on local image characteristics. This dynamic adaptation allows the system to achieve optimal compression efficiency for each region, improving overall compression performance compared to static encoding methods.
Data Source
AI summary
Provided are an image decoding method and an image decoding apparatus, and an image encoding method and an image encoding apparatus which correspond thereto, the image decoding method including: selecting a current block from among a plurality of blocks obtained by dividing a current image; determining a plurality of transform blocks including a first transform block and a second transform block based on the current block; scaling a first direct current (DC) transform coefficient value of the first transform block using a size of the first transform block and a reference transform size to obtain a scaled first DC transform coefficient value; obtaining a prediction transform coefficient value for the second transform block based on a size of the second transform block and the scaled first DC transform coefficient value; determining a second DC transform coefficient value of the second transform block based on the prediction transform coefficient value; and restoring the current block by performing an inverse transform on the second transform block based on the second DC transform coefficient value