Image Compression Coding for Real-Time FPGA Video Processing
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Solution Overview
Problem
Existing image compression standards are complex, slow, and difficult to implement in hardware, leading to high costs and inefficiencies in real-time image transmission.
Innovation Solution
An image compression method and system that performs color space transformation, intra-row differential pulse code modulation coding, and variable length coding using a combination of fixed and dynamic code tables, allowing for parallel processing and reduced algorithm complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If JPEG lossless compression uses a 2D prediction model, then compression effectiveness is improved, but hardware implementation complexity and cost increase significantly
Solution Approach 1:
The patent segments the image processing into independent row-by-row operations, where each row is processed separately using 1D prediction rather than requiring full 2D context. This segmentation eliminates the need to store and process entire preceding rows, dramatically reducing hardware complexity while maintaining compression effectiveness through adaptive prediction within each row.
Solution Approach 2:
The patent transitions from 2D prediction (requiring storage of preceding row data) to 1D prediction (processing only current row with local context). This dimensional reduction simplifies the hardware architecture by eliminating the need for large buffer memories and complex 2D neighbor access, making real-time hardware implementation feasible.
2Loss of information
If Huffman coding or arithmetic coding is used, then compression ratio is improved, but hardware realization becomes complicated
Solution Approach 1:
The patent employs simple fixed-length binary coding instead of complex Huffman or arithmetic coding structures. While individual code lengths are uniform, the overall system achieves good compression through the combination of efficient 1D prediction and straightforward variable-length encoding, avoiding the computational overhead and hardware complexity of adaptive coding schemes.
3Quantity of substance
If compressed codes are stored successively, then storage efficiency is improved, but parallel processing capability is lost
Solution Approach 1:
The patent processes and stores image data in independent row segments that can be handled in parallel. Each row's compression and encoding operations are independent of other rows, enabling multiple rows to be processed simultaneously in hardware pipelines while maintaining efficient sequential storage of the compressed bitstreams.
4Loss of information
If powerful computation capability and large storage capacity are provided, then compression performance is improved, but implementation cost increases
Solution Approach 1:
The patent applies partial action by using simplified 1D prediction on a row-by-row basis rather than full 2D prediction across the entire image. This partial approach achieves sufficient compression performance for most practical applications while dramatically reducing the computation capability and storage capacity requirements, thereby lowering implementation costs.
Data Source
AI summary
An image processing method and system that performs color space transformation on an image to be compressed and obtaining pixel values, performing intra-row differential pulse code modulation coding on the image pixel values to obtain numerical values, and determining whether each of the numerical values is within a preset range. Variable length coding is performed on the numerical value obtained by using a fixed code table if the numerical value is within the range, variable length and by using a dynamic code table if it is not. Low algorithm complexity and fast processing meets the requirement of real-time video transmission. The pixel components of the image can be processed in parallel and adjacent processing steps can be performed in the same clock frequency, thereby remarkably reducing difficulty and cost in FPGA or chip implementation.