Speckle Noise Reduction with SRAD Filter and Automated Windowing Enhancement

This code serves as an enhancement to the SRAD (Speckle Reducing Anisotropic Diffusion) filter, specifically designed for speckle noise removal in digital image processing. The primary innovation lies in its automated windowing capability that intelligently identifies and isolates speckle-contaminated regions within images. In image processing applications, speckle noise presents a significant challenge by degrading image quality and compromising the accuracy of subsequent analysis. The SRAD filter addresses this through anisotropic diffusion principles that preserve edges while reducing noise. This enhanced implementation incorporates region detection algorithms that automatically: 1. Identify speckle patterns using statistical analysis of pixel intensity variations 2. Define optimal window boundaries around noise clusters 3. Apply targeted filtering operations to maintain image structural integrity The automated windowing mechanism employs threshold-based segmentation and morphological operations to precisely locate speckle zones, followed by adaptive filtering parameters that adjust based on local noise characteristics. This approach significantly improves processing efficiency by focusing computational resources only on affected areas, making it particularly valuable for real-time imaging systems and large dataset processing. Key functions include: - Adaptive threshold calculation using noise variance estimation - Connected component analysis for region grouping - Dynamic window sizing based on speckle distribution patterns - Integration with SRAD's partial differential equation solver for coherent denoising This implementation maintains all original SRAD filter advantages while adding intelligent automation that reduces manual parameter tuning and improves batch processing capabilities for medical ultrasound, synthetic aperture radar, and other speckle-prone imaging modalities.