A Novel Approach of Harris Corner Detection of Noisy Images using Adaptive Wavelet Thresholding Technique
This addresses a specific image processing challenge for noisy natural images, but appears incremental as it combines existing techniques.
The paper tackles corner detection in noisy images by applying adaptive wavelet thresholding for denoising, resulting in improved feature extraction for object tracking and recognition.
In this paper we propose a method of corner detection for obtaining features which is required to track and recognize objects within a noisy image. Corner detection of noisy images is a challenging task in image processing. Natural images often get corrupted by noise during acquisition and transmission. Though Corner detection of these noisy images does not provide desired results, hence de-noising is required. Adaptive wavelet thresholding approach is applied for the same.