Image Encoder Boundary Compression Using Previous Frame Reference Pixels
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Solution Overview
Problem
Existing image compression methods, such as Differential Pulse Code Modulation (DPCM), face challenges in compressing image data at boundaries where no peripheral pixel data is available, leading to errors and increased compression loss.
Innovation Solution
An image encoder that utilizes reference pixel data from a previous frame image to compress subsequent frames, using difference values between reference and original pixel data to generate a bitstream, which is then reconstructed to maintain boundary pixel information, thereby reducing compression loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If DPCM compression is applied to boundary pixels using peripheral pixel data, then compression efficiency is improved, but boundary pixels without peripheral data cannot be compressed and errors propagate
Solution Approach 1:
The patent stores boundary pixel data from the previous frame in advance before compression is needed. This preliminary storage of reference boundary pixel data enables the compression algorithm to have available data for boundary pixels of the current frame, eliminating the problem of missing peripheral data at boundaries while maintaining compression efficiency.
Solution Approach 2:
The patent creates a copy of the boundary pixel data from the previous frame and stores it in a dedicated buffer. This copied reference data is then used during compression of the current frame's boundary pixels, allowing the system to replicate the beneficial compression approach used for internal pixels at the boundaries without requiring actual peripheral boundary pixels from the current frame.
2Loss of substance
If peripheral pixel data is used for DPCM compression, then compression ratio is improved, but compression loss increases when peripheral data is unavailable or inaccurate
Solution Approach 1:
The patent implements a feedback mechanism where boundary pixel data from previously compressed frames is stored and fed back into the compression process. This feedback loop ensures that the most recent boundary data is always available as reference, allowing the compression algorithm to maintain accuracy while achieving high compression ratios through differential encoding.
Solution Approach 2:
The patent changes the reference parameter source for boundary pixels from spatial neighbors (which may not exist) to temporal neighbors (previous frame boundary pixels). This parameter change in the reference data source allows the system to maintain consistent compression performance across all pixels including boundaries, reducing both data size and information loss.
Data Source
AI summary
The present disclosure provides an image encoder. The image encoder is configured to encode an original image and reduce compression loss. The image encoder comprises an image signal processor and a compressor. The image signal processor is configured to receive a first frame image and a second frame image and generates a compressed image of the second frame image using a boundary pixel image of the first frame image. The image signal processor may include memory configured to store first reference pixel data which is the first frame image. The compressor is configured to receive the first reference pixel data from the memory and generate a bitstream obtained by encoding the second frame image based on a difference value between the first reference pixel data and the second frame image. The image signal processor generates a compressed image of the second frame image using the bitstream generated by the compressor.