Tone Mapping With Adaptive Weights to Reduce Image Boundary Defects
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Solution Overview
Problem
Existing image processing techniques, such as tone mapping, often result in image saturation and loss of information in dark and bright parts, leading to line-shaped defects and deteriorated image quality.
Innovation Solution
An image processing apparatus that applies noise to input image data, calculates weights based on luminance differences, and generates output data using adjusted weights to minimize defects and enhance image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If one tone curve is used for tone mapping, then the processing is simple, but the image data becomes saturated and information in dark and bright parts is lost
Solution Approach 1:
The patent divides the image processing into multiple segments by applying different tone curves to different luminance regions. The processing apparatus separates the image into multiple luminance ranges and applies specific tone curves to each range, preventing saturation while preserving information in both dark and bright parts.
Solution Approach 2:
The patent implements local quality by using different tone curves for different luminance regions of the image. Each region receives a customized tone curve based on its luminance characteristics, ensuring optimal processing for dark, mid, and bright areas rather than applying a uniform transformation.
2Productivity
If conventional tone mapping is performed, then the processing is fast, but line-shaped defects occur and image quality deteriorates
Solution Approach 1:
The patent performs preliminary actions by calculating luminance values and determining appropriate tone curves before applying the tone mapping. This preparation step ensures that the correct tone curve is selected for each luminance region, preventing line-shaped defects and maintaining image quality while keeping the overall process efficient.
Solution Approach 2:
The patent introduces dynamics by adaptively selecting and adjusting tone curves based on the luminance characteristics of different image regions. The processing is not static but dynamically adapts to local luminance conditions, preventing artifacts while maintaining processing speed through efficient curve selection.
Data Source
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AI summary
An image processing apparatus and a method of operating the same are provided. The image processing apparatus includes a luminance calculator configured to convert input image data into luminance image data including luminance values of a plurality of pixels, a noise calculator configured to generate sum values obtained by adding noise values corresponding to neighboring pixels around a target pixel of the plurality of pixels, to the luminance values of the neighboring pixels, a tone mapper configured to generate first and second mapping data by applying a first tone curve and a second tone curve to a luminance value of the target pixel and the sum values of the neighboring pixels, a characteristic value calculator configured to calculate first and second weights for the first and second mapping data, a gain blender configured to adjust the first and second weights and generate output image data, and a display device configured to display the output image data.