Block-Based Image Contrast Enhancement With Reduced Memory
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Solution Overview
Problem
Existing image processing methods require significant memory to enhance contrast through block-based histogram equalization, making them inefficient in terms of memory usage and practical implementation.
Innovation Solution
An image processing apparatus and method that divides an image into blocks, calculates and uses a weighted summation of minimum, maximum, average, lower average, and upper average values from previous images to generate output values, reducing the need for extensive memory storage by utilizing only key statistical values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If block-based histogram equalization is used to enhance image contrast, then image quality is improved, but memory requirements increase significantly
Solution Approach 1:
The patent extracts only the essential statistical parameters (minimum, maximum, average values) from image blocks, discarding the need to store complete histograms. This extraction approach maintains contrast enhancement capability while dramatically reducing memory consumption by storing only 3 values per block instead of full histogram data.
Solution Approach 2:
The patent changes the representation parameters from complete histograms to simplified statistical moments (min, max, average). This parameter transformation allows the system to maintain the essential contrast information needed for image enhancement while using significantly less memory to store the reduced parameter set.
2Measurement precision
If conventional histogram equalization is applied to the entire image, then uniform brightness distribution is achieved, but processing complexity and memory usage increase
Solution Approach 1:
The patent divides the image into multiple blocks and applies histogram equalization independently to each block using simplified statistical parameters. This segmentation approach reduces processing complexity and memory requirements compared to global histogram equalization, while still achieving effective contrast enhancement in each local region.
Solution Approach 2:
The patent applies a simplified version of histogram equalization that uses only partial information (min, max, average values) rather than the complete histogram distribution. This partial action approach achieves sufficient contrast enhancement for practical purposes while avoiding the computational and memory overhead of full histogram processing.
Data Source
AI summary
Provided are an image processing apparatus and method. The image processing apparatus divides an image into a plurality of blocks, and enhances contrast in units of blocks by using a minimum value, a lower average value, an average value, an upper average value, and a maximum value of each block in the image.