Image Graininess Evaluation Using Entropy of Blurred Pixel Differences
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image evaluation techniques require a comparative image and are not effective in evaluating image graininess regardless of image size, necessitating a method to objectively assess image graininess using only the evaluation-target image.
Innovation Solution
An image evaluation device comprising a blurer, differentiator, scanner, and calculator that creates a blurred image, calculates pixel value differences, and computes entropy from these differences to determine the graininess of an image, allowing for scanning along various paths including left-to-right, top-to-bottom, and space-filling curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a comparative image is used to evaluate image graininess, then the evaluation can be performed, but the evaluation process becomes complex and requires additional image data
Solution Approach 1:
The patent extracts only the necessary information from the image (pixel value differences after blurring) to evaluate graininess, eliminating the need for complex comparative image processing while maintaining evaluation accuracy
Solution Approach 2:
The evaluation method uses only the evaluation-target image itself (by creating a blurred version of it) to determine graininess, making the system self-sufficient without requiring external comparative images or additional data
2Measurement precision
If traditional evaluation methods are used, then image graininess can be assessed, but the evaluation is affected by image size variations
Solution Approach 1:
The patent changes the parameter of image representation by using pixel value differences in a blurred image, which creates a size-independent metric for graininess evaluation that works consistently across different image dimensions
3Measurement precision
If multiple images are evaluated for selection, then the best image can be chosen, but the evaluation time and computational resources increase
Solution Approach 1:
The patent applies partial action by using only the essential blurring and pixel difference calculation steps needed for graininess evaluation, avoiding excessive processing while maintaining sufficient accuracy for effective image selection
Data Source
AI summary
An image evaluation device (101) properly evaluating the graininess (or roughness) of an image is provided. The blurer (102) creates a second image b by blurring a first image a. The differentiator (103) creates a third image c presenting the difference between the first image a and second image b. The pixel value of each pixel of the third image c presents the difference in pixel value between the pixels at the same position in the first image a and second image b. The scanner (104) scans the pixels contained in the third image c, obtains the differences in pixel value between adjoining pixels, and obtains the respective probabilities of occurrence of the differences. The calculator (105) calculates the entropy from the obtained, respective probabilities of occurrence of the differences. The outputter (106) outputs the entropy as the evaluation value of the graininess (or roughness) of the first image.