Directional Noise Removal in Image Processing via Orthogonal Filtering
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Solution Overview
Problem
Existing methods for removing directional noise from images, such as those obtained by line-scanning, fail to accurately detect minute luminance shading due to subtracting average values, which can distort true values and overlook device-specific information.
Innovation Solution
An image processing device and method utilizing a high-pass filter in one direction and a low-pass filter in a perpendicular direction, with an addition unit to combine the filtered images, effectively removing directional noise while preserving luminance information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If an average value of a predetermined region is subtracted from target pixel values to remove directional noise, then the noise is removed, but minute shading of luminance information is lost and true values are distorted
Solution Approach 1:
The image processing is segmented into two independent filtering operations: high-pass filtering in the first direction to remove directional noise, and low-pass filtering in the perpendicular direction to preserve luminance information. Each filtering operation processes the image separately, allowing targeted noise removal without compromising overall image fidelity.
Solution Approach 2:
The solution transitions from a single-direction processing approach to a two-dimensional filtering strategy. By applying high-pass filtering in one direction and low-pass filtering in the perpendicular direction, the method utilizes both spatial dimensions to simultaneously achieve noise removal and information preservation.
2Object-affected harmful factors
If a high-pass filter is applied in the first direction to remove directional noise, then noise is removed, but luminance information may be affected
Solution Approach 1:
Different filtering characteristics are applied in different directions: high-pass filtering is applied specifically in the first direction where directional noise occurs, while low-pass filtering is applied in the perpendicular direction to preserve luminance information. This directional differentiation allows targeted noise removal while maintaining local image quality.
Solution Approach 2:
The filtering approach combines two different filter types (high-pass and low-pass) applied in perpendicular directions to create a composite filtering effect. This composite approach leverages the strengths of both filter types: high-pass filtering removes directional noise while low-pass filtering preserves luminance information.
Data Source
AI summary
An image processing device for removing a noise having directionality in a first direction from an image containing the noise without affecting information on minute shading of luminance of the image, including: a high-pass filter unit configured to perform filtering processing on an image containing a noise having directionality in a horizontal direction with a high-pass filter in the horizontal direction; a low-pass filter unit configured to perform filtering processing on the image in a vertical direction with a low-pass filter; and an addition unit configured to add an image processed by the high-pass filter unit and an image processed by the low-pass filter unit.