Invariant Brightness Digital Image Filter for Contrast Enhancement
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Solution Overview
Problem
Existing digital image filters fail to effectively enhance image contrast without artificially increasing the brightness of dark objects, leading to noise artifacts and inadequate contrast enhancement in low-light environments.
Innovation Solution
A method and filter that determine an invariant brightness level and apply a contrast adjustment formula (Iout = (Iin - L)C + L) to each pixel, where Iin is input brightness, Iout is output brightness, C is a contrast constant, and L is the invariant brightness level, ensuring that dark objects remain unchanged while brighter pixels are enhanced, and using histogram equalization to redistribute luminance values evenly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If conventional digital image filters are used to enhance contrast, then image contrast is improved, but the brightness of dark objects is artificially increased and noise artifacts are generated
Solution Approach 1:
The patent applies different processing to different regions of the image histogram. Specifically, it identifies dark objects (low brightness values) and applies a different contrast enhancement approach compared to brighter regions. The method uses adaptive contrast enhancement that preserves the brightness of dark objects while enhancing the contrast of brighter pixels, thereby avoiding the generation of noise artifacts in dark regions.
Solution Approach 2:
The patent dynamically adjusts the contrast enhancement parameters based on the image content. It calculates adaptive contrast values for different brightness ranges and applies them selectively. By changing the enhancement parameter from a fixed global value to a dynamic, content-dependent value, the method enhances contrast without artificially increasing the brightness of dark objects or introducing noise.
2Illumination intensity
If conventional contrast enhancement methods are applied, then image contrast is improved, but dark objects in low-light environments have inadequate enhancement
Solution Approach 1:
The patent implements dynamic contrast enhancement that adapts to the lighting conditions of the image. It calculates the mean and standard deviation of pixel brightness values and uses these statistics to determine appropriate enhancement parameters. This dynamic approach ensures reliable contrast enhancement across different lighting conditions, including low-light environments, by adjusting the enhancement strength based on the actual image characteristics.
Solution Approach 2:
The patent employs feedback mechanisms to evaluate the effectiveness of contrast enhancement and adjust parameters accordingly. It analyzes the histogram of brightness values and uses this information to refine the enhancement process. The feedback loop ensures that dark objects in low-light conditions receive appropriate enhancement while maintaining the natural appearance of the image.
3Productivity
If simple brightness multiplication is used, then processing speed is maintained, but contrast enhancement is inadequate and brightness is artificially increased
Solution Approach 1:
The patent segments the brightness range into different intervals and applies different contrast enhancement parameters to each segment. Instead of applying a single global multiplication factor, it divides the histogram into multiple ranges (e.g., dark, mid-range, bright) and applies selective enhancement to each. This segmentation approach maintains processing efficiency while significantly improving contrast enhancement quality.
Solution Approach 2:
The patent applies partial contrast enhancement only where needed, rather than uniformly enhancing the entire image. It identifies regions that require enhancement (based on histogram analysis) and applies contrast enhancement selectively to those regions, while leaving other regions unchanged. This partial action approach maintains processing speed while achieving adequate contrast enhancement without artificially increasing overall brightness.
Data Source
AI summary
Digital image filters and related methods for image contrast enhancement are disclosed. According to one aspect of the method, an invariant brightness level is initially determined. For each pixel of an input image, the invariant brightness level is subtracted from the input brightness of the pixel. The resulting value is multiplied with a contrast adjustment constant. After that, the invariant brightness level is added. Further aspects of the method can involve histogram equalization.