Display Compensation Data Compression Using Area-Specific DCT Encoding

The patent applies different compression parameters and methods to different pixel areas. Normal pixels use DCT-based lossy compression with quantization, while important pixels (highlighted pixels) use lossless compression or higher precision DCT to maintain image quality where it matters most, thereby reducing overall storage requirements while maintaining perceived image quality

The patent implements area-specific compression strategies where different portions of the image receive different levels of compression. Normal areas undergo aggressive DCT compression, while important areas (such as regions with high-frequency information or semantically significant content) are preserved with lossless or high-quality compression, optimizing the balance between storage efficiency and image quality

The patent dynamically adjusts compression parameters including quantization step sizes, DCT block sizes, and compression ratios based on the importance of different pixel areas. Important pixels use smaller quantization steps or lossless compression to prevent artifacts, while normal pixels use more aggressive compression, thereby reducing storage while minimizing image abnormalities

The patent introduces an importance determination module that acts as an intermediary between the compression process and the final image output. This module identifies and flags important pixels that require special handling during compression, ensuring they are preserved with higher fidelity while allowing normal pixels to be compressed more aggressively

The patent divides the image into different areas (normal pixels and important pixels) and applies different compression algorithms or parameters to each area. Important pixels are identified based on criteria such as edge detection, high-frequency content, or semantic importance, and are processed with lossless or high-quality DCT compression to preserve critical information

The patent segments the image data into different categories (normal pixels and important pixels) before compression. This segmentation allows the system to apply appropriate compression strategies to each segment, ensuring that critical pixel information is preserved while still achieving overall compression efficiency