Overlapped Curve Mapping for Histogram-Based Local Tone and Contrast
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Solution Overview
Problem
Existing global histogram equalization techniques struggle to effectively improve contrast in images with both dark and bright regions, often resulting in halo effects and blocky artifacts due to significant tone and contrast mapping curve differences between blocks.
Innovation Solution
The method involves spatial low-passing of block-based mapping curves with corresponding surrounding blocks and applying overlapped curve mapping to smooth the mapping curve, using bilinear interpolation and weighted averages to generate new pixel values that mitigate blockiness and halo effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If local histogram equalization is applied to each block, then local contrast is improved, but halo effects and blocky artifacts occur due to significantly different tone and contrast mapping curves for each block
Solution Approach 1:
The patent combines mapping curves from multiple overlapping blocks to generate a unified mapping curve. Instead of applying separate mapping curves to each block, the invention merges the curves through weighted averaging, where pixels in overlapping regions contribute to multiple blocks' histograms. This integration smooths transitions between blocks and eliminates the discontinuities that cause halo effects and blocky artifacts.
Solution Approach 2:
The patent implements local quality by allowing different regions of the image to have different mapping characteristics while maintaining overall coherence. Each block's histogram is computed locally, but the mapping curves are blended using spatial weighting functions that ensure smooth transitions. This approach preserves local contrast enhancement while preventing the harmful artifacts that arise from abrupt changes between blocks.
2Manufacturing precision
If global histogram equalization is used, then overall contrast is improved, but contrast in both dark and bright regions cannot be effectively enhanced
Solution Approach 1:
The patent divides the image into multiple blocks and computes histograms separately for each block. This segmentation allows the algorithm to adapt to local characteristics, enabling effective contrast enhancement in both dark and bright regions. By processing blocks independently and then blending their mapping curves, the invention overcomes the limitation of global histogram equalization which treats the entire image uniformly.
Solution Approach 2:
The patent introduces dynamic adaptation by computing histograms and mapping curves for each block based on its local content. The mapping process is not static but adapts to local variations in brightness and contrast. This dynamic approach allows the system to enhance contrast in dark regions without oversaturating bright regions, providing versatility across different image regions.
Data Source
AI summary
Methods and apparatuses are disclosed herein for performing tone mapping and/or contrast enhancement. In some examples, a block mapping curve is low-pass filtered with block mapping curves of surrounding blocks to form a smoothed block mapping curve. In some examples, overlapped curve mapping of block mapping curves, including smoothed block mapping curves, is performed, including weighting, based on a pixel location, block mapping curves of a group of blocks to generate an interpolated block mapping curve and applying the interpolated block mapping curve to a pixel to perform ton mapping and/or contrast enhancement.