Denoising Grayscale and Binary Images Using Morphological Filters
- Login to Download
- 1 Credits
Resource Overview
Detailed Documentation
Morphological filters mentioned in the text can be applied to denoise both grayscale and binary images. These filters utilize morphological operations to improve image quality by eliminating noise and unnecessary details. In image processing, denoising is a crucial step for enhancing image clarity and readability. Morphological filtering serves as a common denoising approach, leveraging the shape and structure characteristics within images to perform filtering effectively. Implementation typically involves operations like erosion and dilation—for example, using a structuring element to remove small noise points in binary images through erosion, followed by dilation to restore the main structures. For grayscale images, morphological open and close operations can smooth bright or dark noise while preserving edges. Thus, when processing grayscale or binary images, employing morphological filters is a practical and efficient option worth considering.
- Login to Download
- 1 Credits