Pixel-Difference Image Compression for HDR Synthesis
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Solution Overview
Problem
Existing imaging devices face challenges in generating high dynamic range (HDR) images due to bandwidth and power consumption limitations, especially when capturing and processing multiple images with different exposure settings, which exceed the capacity of current image processing systems.
Innovation Solution
The proposed solution involves compressing images based on pixel differences between reference and target images, particularly using lossless compression techniques to reduce bandwidth and power consumption during HDR image synthesis, by normalizing pixel values and encoding differences in fewer bits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images with different exposure settings are captured and processed to generate HDR images, then image quality and dynamic range are improved, but bandwidth and power consumption increase beyond system capacity
Solution Approach 1:
The patent extracts only the essential information needed for HDR image generation by compressing images to retain only significant pixel differences and features. This extraction reduces the data volume transmitted and processed, thereby lowering bandwidth and power consumption while preserving the necessary image quality for HDR synthesis.
Solution Approach 2:
The patent changes the parameter of image data representation by transforming full-resolution images into compressed formats that encode only the differences between consecutive frames. This parameter transformation reduces data size and processing requirements while maintaining the essential information needed for high dynamic range image generation.
2Use of energy by moving object
If images are compressed to reduce bandwidth and power consumption, then energy efficiency is improved, but data loss may occur
Solution Approach 1:
The patent applies preliminary compression to images before they are transmitted or stored, reducing their size in advance. This preliminary action minimizes the data that needs to be processed later, reducing overall power consumption while the compression algorithm is designed to preserve critical image information needed for HDR generation.
Solution Approach 2:
The compression system incorporates feedback mechanisms that monitor image quality and adjust compression parameters accordingly. This feedback ensures that compression does not lose critical information needed for HDR synthesis, maintaining data accuracy while optimizing power consumption based on actual image content requirements.
Data Source
AI summary
Disclosed are systems, apparatuses, processes, and computer-readable media to capture images with subjects at different depths of fields. For instance, a method of processing image data includes obtaining a first image captured using an image sensor with a first exposure. The method may further include obtaining a second image captured using the image sensor with a second exposure. The method may include compressing the second image based on a comparison of the second image with the first image and storing the compressed second image in a memory. The method may further include obtaining the compressed second image from the memory and decompressing the compressed second image based on a difference between the compressed second image and the first image. The method may further include generating a combined image at least in part by combining the first image and the second image.