Image Contrast Enhancement via Block Segmentation and Luminance Interpolation
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Solution Overview
Problem
Conventional image enhancement methods face limitations in real-time applications due to memory and processing time constraints, and fail to accurately enhance contrast by distinguishing between distorted and undistorted pixels, leading to potential flickering in video frames and inefficient use of window or filter sizes.
Innovation Solution
The method divides the input image into blocks, calculates average luminance values, and interpolates peripheral luminance values using a Look-Up Table, allowing for efficient contrast enhancement by varying luminance increases and decreases based on unique and peripheral luminance values, thereby reducing processing time and memory requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sliding window or low pass filter is used to calculate average brightness around input pixels, then contrast enhancement is achieved, but memory and processing time requirements increase significantly
Solution Approach 1:
The patent divides the image into multiple blocks and processes each block independently to calculate average luminance values. This segmentation approach replaces the traditional sliding window method, reducing processing time while maintaining contrast enhancement accuracy. The image is divided into manageable segments that can be processed in parallel or sequentially without requiring continuous overlap calculations.
Solution Approach 2:
The patent pre-calculates average luminance values for each block before performing contrast enhancement. This preliminary calculation of luminance statistics for each block allows the subsequent contrast enhancement to proceed more efficiently without repeatedly calculating average brightness during the enhancement process, thus reducing overall processing time.
2Measurement precision
If a sliding window or low pass filter is used to calculate average brightness around input pixels, then contrast enhancement is achieved, but memory requirements increase
Solution Approach 1:
The patent segments the image into discrete blocks and stores only the average luminance values for each block rather than maintaining full sliding window data. This segmentation reduces memory requirements significantly while preserving the necessary information for contrast enhancement, as only the aggregated luminance statistics per block are needed rather than pixel-level data for all window positions.
3Measurement precision
If enhancement gain is applied to correct distorted luminance signal, then brightness correction is achieved, but flickering phenomenon occurs in video frames
Solution Approach 1:
The patent applies different enhancement gains to different blocks based on their specific luminance characteristics. Each block receives a customized enhancement gain calculated from its average luminance value, rather than applying a uniform gain across the entire image. This local adaptation prevents flickering by avoiding abrupt brightness changes while maintaining accurate luminance correction in each region.
Solution Approach 2:
The patent dynamically adjusts enhancement parameters based on the average luminance values calculated for each block. By changing the enhancement gain parameter according to the local luminance characteristics of each block, the system achieves accurate brightness correction while maintaining frame stability and preventing flickering effects in video sequences.
4Measurement precision
If uniform enhancement gain is applied to correct distorted luminance, then brightness correction is achieved, but undistorted image brightness enhancement is omitted
Solution Approach 1:
The patent applies different enhancement strategies to different blocks based on their luminance distortion characteristics. Blocks with distorted luminance receive correction enhancement, while blocks with undistorted luminance receive brightness enhancement. This local differentiation ensures that both correction and brightness enhancement are achieved without omitting either function.
Data Source
AI summary
A method of enhancing a contrast and an apparatus for enhancing a contrast are provided. The method of enhancing the contrast includes: dividing an image into a plurality of blocks and calculating an average luminance value of each block; interpolating a peripheral luminance value for each input pixel of the image by using the average luminance value; and enhancing the contrast of the input pixel by using the interpolated peripheral luminance value of the input pixel and a unique luminance value of the input pixel.