Radar Image Processing Using Layover-Aware Search Range for Speckle Reduction
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Solution Overview
Problem
The existing SAR-BM3D technique for reducing speckle noise in radar images faces inefficiencies in calculating similar blocks due to a wide search range, which affects filtering performance and increases computational cost.
Innovation Solution
A radar image processing device and method that determines a search range based on a reference block and the layover direction, allowing for efficient extraction of similar blocks and improved speckle reduction processing by using these blocks for filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a wide search range is used to detect similar blocks in SAR-BM3D, then more similar blocks can be detected improving filtering performance, but the calculation amount increases significantly
Solution Approach 1:
The search range is segmented into multiple candidate ranges with different sizes. Instead of using a single wide search range, the method divides the search space into several smaller candidate ranges, which reduces the calculation amount while still allowing detection of similar blocks across different spatial scales.
Solution Approach 2:
The search range is made dynamic and adaptive rather than fixed. The method automatically adjusts the search range size based on local image characteristics and speckle patterns, allowing the algorithm to expand or contract the search area as needed to maintain filtering performance while minimizing unnecessary calculations.
2Ease of operation
If a square range centered on reference block is used as search range, then the search process is simple, but it is not necessarily optimal for detecting similar blocks and reduces filtering efficiency
Solution Approach 1:
The search range is adapted to local image characteristics rather than using a uniform square shape. The method determines candidate ranges based on local speckle patterns and structural features, making the search process more effective in different regions of the image while maintaining reasonable computational complexity.
Solution Approach 2:
The search range parameters (size, shape, orientation) are changed and optimized based on local image conditions. Instead of fixed square ranges, the method adjusts range parameters to match local structural characteristics, improving similar block detection efficiency without significantly complicating the search process.
Data Source
AI summary
A radar image processing device includes at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: determine a search range based on a reference block and a layover direction, the reference block being set as an area of interest in a radar image generated from data obtained by an imaging radar, the layover direction being a direction in which layover occurs in the radar image and being estimated from an incident direction of an electromagnetic wave used for observation by the imaging radar; extract a similar block that is similar to the reference block and included in the search range by searching the search range; and perform filtering processing for reducing speckles generated in the radar image by using the reference block and the extracted similar block.