Resolved Edge Case Handling and Performance Improvements in Image Processing Functions.

[sayantann7]

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Issue Description:

Several issues related to edge case handling and performance inefficiencies were resolved in the image processing functions. Below is a summary of how these problems were fixed:

Fixes

1. Fixed Kernel Assignment in opening_filter and transform The kernel was properly initialized and assigned in both functions to ensure consistent behavior when applying filters.
2. Dynamic Padding for Kernel in transform Dynamic padding was added to handle kernel size variations, ensuring that transformations apply correctly without cropping or distorting the image.
3. Handled Edge Cases in normalize_array Added a check to prevent division by zero during array normalization, ensuring that values are handled safely in edge scenarios.
4. Removed Unnecessary Type Casting in get_distances Type casting to np.uint8 was removed to prevent clipping of values, preserving the accuracy of distance calculations.
5. Implemented Error Handling for Invalid Parameters A validation step was introduced for parameters["format"] to handle invalid inputs gracefully, preventing unexpected function failures.
6. Improved Clarity in binary_mask Return Values Return values were renamed to improve clarity and reduce confusion in their usage, making the function more intuitive.
7. Validated Pixel Ranges in matrix_concurrency Checks were added to ensure pixel ranges are valid, preventing out-of-bounds errors during array manipulation.
8. Optimized Array Operations in haralick_descriptors Optimized array operations using vectorization techniques, improving performance and reducing processing time.