Image Calibration via Dynamic Hash Table Dithering
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Solution Overview
Problem
Images transformed between high and low resolutions often exhibit quantization errors, leading to visual faults such as banding effects due to differences in color depth between the original image and the display device.
Innovation Solution
A calibrating device and method that uses a dithering process by adding randomly generated hash values to pixel points of the image, adjusting these values based on a time parameter to prevent the same hash value from being applied to the same pixel point in sequential images, thereby eliminating quantization errors and smoothing the output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the color depth of the original image is upgraded or downgraded to match the displayer specification, then the image compatibility with the displayer is improved, but quantization errors are introduced causing visual faults such as banding effects
Solution Approach 1:
The patent changes the color depth parameter of the image to match the displayer specification (e.g., converting 6-bit or 10-bit images to 8-bit). This parameter transformation enables compatibility with standard displays while the subsequent dithering process mitigates the quality degradation through controlled error distribution.
Solution Approach 2:
The patent introduces dithering as an intermediary process between image transformation and display. By adding carefully calculated noise patterns, dithering acts as a mediator that smooths the transition and masks quantization errors, preventing direct visualization of banding effects while maintaining the transformed color depth.
2Productivity
If the same hash value is added to the same pixel point in sequential images, then the processing speed is improved, but the calibration effect is reduced due to repeated patterns becoming visible
Solution Approach 1:
The patent implements dynamic hash table adjustment by shifting the hash table based on the time parameter (frame number) of sequential images. This dynamic transformation ensures that while the same pixel point receives a hash value from the same hash table structure, the actual hash value changes with each frame, preventing repetitive patterns while maintaining efficient hash table-based processing.
Solution Approach 2:
The patent applies periodic shifting to the hash table at regular intervals (each frame). This periodic transformation of the hash table structure ensures that the calibration process remains effective across sequential images by systematically varying the hash values applied to each frame, preventing visual artifacts from repetition.
Data Source
AI summary
A calibrating device of calibrating a real-time image through a dithering process including a receiving unit, a storing unit, a displacing module, a computing module, and an outputting unit is disclosed. The receiving unit receives a real-time image from an image sensor and records a time parameter of the image. The storing unit stores a hash table that records multiple hash values used to calibrate the image. The displacing module shifts the multiple hash values in the hash table to generate an adjusted hash table. The computing module obtains a corresponding hash value from the adjusted hash table for each pixel point of the image in accordance with the coordinates of each pixel point, and respectively adds the corresponding hash value to the pixel value of each pixel point of the image to generate a calibrated image. The outputting unit outputs the calibrated image.