Image Tone Correction via Histogram Peak Adjustment
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Solution Overview
Problem
Existing image processing methods, such as those described in Patent Literature 1, face challenges in correcting image quality by separately adjusting color and luminance, leading to incomplete correction due to difficulties in cutting out image data accurately, which results in reduced precision and inability to correct color unevenness effectively.
Innovation Solution
An image processing apparatus that divides captured images into partial images, generates histograms for each color component, determines adjustment values based on histogram peaks, and uses tone correction data to correct each partial image, thereby simplifying the process and achieving desired image quality without cutting out the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image data of the actual target part is cut out for correction, then color and luminance correction can be performed, but the process becomes troublesome and exactness of correction is greatly reduced due to failure in cutting out
Solution Approach 1:
The invention extracts only the necessary correction parameters (luminance histogram and color difference histogram) from the captured image without physically cutting out or segmenting the actual target part. This allows correction to be performed on the entire image while focusing computational effort on relevant statistical distributions, thereby maintaining exactness while reducing process complexity.
Solution Approach 2:
The correction apparatus performs both color correction and luminance correction functions within a single integrated system that operates on the entire captured image. By generating histograms that capture both color and luminance information simultaneously, the system achieves multi-functional correction without requiring separate processing steps for different image regions.
2Reliability
If separate color correction and luminance correction are performed, then both aspects can be adjusted, but the correction process becomes troublesome and time-consuming
Solution Approach 1:
The invention merges color correction and luminance correction into a single integrated process by simultaneously generating both luminance histogram and color difference histogram from the captured image. These histograms are then used together to determine correction parameters that address both color and luminance issues in one unified correction step, maintaining completeness while reducing time loss.
Solution Approach 2:
The system performs preliminary analysis by generating histograms that capture both color and luminance characteristics before actual correction is applied. This preliminary histogram generation allows the determination of optimal correction parameters in advance, enabling both color and luminance correction to be executed efficiently in a single operation rather than requiring multiple sequential adjustments.
3Measurement precision
If the entire captured image is processed for correction, then cutting out failures are avoided, but color unevenness cannot be corrected effectively
Solution Approach 1:
The invention applies local quality correction by using color difference histograms that capture spatial variations in color throughout the captured image. While processing the entire image to avoid cutting out failures, the system generates histogram data that reflects local color characteristics, enabling effective correction of color unevenness through statistically-based correction parameters derived from the overall image distribution.
Data Source
AI summary
An image processing apparatus includes: a dividing process section (122) configured to divide a captured image into a plurality of partial images; a histogram creating section (123) configured to create a histogram representing a distribution of the number of pixels for density values with respect to each color component of each of the partial images; an adjustment value calculating section (124) configured to determine, for each of the partial images, an adjustment value based on a peak in the histogram; an adjusting section (127) configured to generate, for each of the partial images, tone correction data by replacing a specific input value in reference data with the adjustment value; and a correction process section (128) configured to generate a corrected image by tone-correcting each of the partial images with use of the tone correction data.