Image Processing False Contour Removal via Probability Model
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Solution Overview
Problem
Existing image processing technologies fail to effectively remove false contours from images, which degrade image quality and are challenging to distinguish from true contours.
Innovation Solution
An image processing apparatus and method utilizing a probability model to optimize pixel values and gradient values, generating a decontour map to combine with the original image, thereby removing false contours and improving image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing image processing technologies are used, then processing speed is maintained, but false contours cannot be effectively removed
Solution Approach 1:
The patent segments the image processing task into multiple stages: obtaining initial pixel values, calculating gradient values, computing probability values for each pixel, and generating the final decontoured image. This segmentation allows complex false contour removal to be achieved through manageable sequential steps without sacrificing processing speed.
Solution Approach 2:
The patent performs preliminary actions by obtaining initial pixel values and gradient values before the main processing. The probability model is prepared in advance, and initial estimates are calculated beforehand, which accelerates the overall process by avoiding iterative refinement during critical processing stages.
2Reliability
If complex processing algorithms are applied to remove false contours, then image quality improves, but computational complexity increases
Solution Approach 1:
The patent replaces complex iterative mechanical processing with a probabilistic model-based approach. Instead of using multiple rounds of complex filtering and adjustment, the system calculates probability values directly based on gradient information and pixel intensity relationships, significantly reducing computational complexity while maintaining high image quality.
Solution Approach 2:
The patent changes the fundamental parameter from direct pixel manipulation to probability-based decision making. By computing probability values that represent the likelihood of each pixel being a false contour, the system achieves sophisticated image quality improvement through a single pass of probability calculation rather than multiple complex processing stages.
3Measurement precision
If comprehensive probability modeling is performed for each pixel, then false contour detection accuracy improves, but memory requirements increase
Solution Approach 1:
The patent extracts only the essential information needed for false contour detection: gradient values and probability values. Instead of storing and processing all possible image characteristics, the system extracts and processes only the critical parameters related to contour detection, minimizing memory requirements while maintaining high detection accuracy.
Solution Approach 2:
The patent performs partial action by calculating probability values only for pixels that are likely to be false contours based on gradient thresholds. Instead of comprehensively processing every pixel in the image, the system focuses computational resources on suspicious regions, reducing memory usage while maintaining detection accuracy for actual false contours.
Data Source
AI summary
An image processing apparatus, including a memory configured to store one or more instructions; and at least one processor configured to execute the one or more instructions to: based on a first image and a probability model, optimize an estimated pixel value and estimated gradient values of each pixel of an original image corresponding to the first image, obtain an estimated original image based on the optimized estimated pixel value of the each pixel of the original image, obtain a decontour map based on the optimized estimated pixel value and the estimated gradient values of the each pixel of the original image, and generate a second image by combining the first image with the estimated original image based on the decontour map.