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Generalized PCM coding of images
Summary
Generalized Pulse-Code Modulation (GPCM) improves image compression efficiency over standard Pulse-Code Modulation (PCM) by adaptively removing bits. This novel algorithm offers better performance based on image content and available computational resources.
Area of Science:
- Digital Signal Processing
- Image Compression
- Data Encoding
Background:
- Pulse-code modulation (PCM) with embedded quantization offers simple bitstream rate reduction by removing least significant bits.
- However, standard PCM exhibits poor coding efficiency for image data.
Purpose of the Study:
- To introduce a Generalized Pulse-Code Modulation (GPCM) algorithm for enhanced image compression.
- To improve coding efficiency compared to traditional PCM by adaptively removing bits.
Main Methods:
- Developed a GPCM algorithm that selectively removes bits from image codewords.
- The bit removal strategy is based on codeword position and image statistics.
- Algorithm complexity is adjustable to suit available computational resources.
Main Results:
- GPCM demonstrates superior performance over standard PCM for image compression.
- The performance gain is contingent upon the compression rate, encoding complexity, and image inter-pixel correlation.
- Experimental results validate the effectiveness of the adaptive bit removal strategy.
Conclusions:
- GPCM offers a more efficient and adaptable approach to image compression compared to PCM.
- The algorithm's flexibility allows for optimization across various applications and resource constraints.
- GPCM represents a significant advancement in source coding for digital images.
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