Tutorial 34 - Image filtering in python - Bilateral filter for image denoising

In microscopy, Gaussian noise arises from many sources including electronic components such as detectors and sensors. In addition, salt & pepper noise may also show up due to errors in analog to digital conversion. Therefore, image denoising is one of the primary pre-processing operations that a researcher performs before proceeding with extracting information out of these images. This tutorial explains Bilateral filter and walks you through the process of writing a couple of lines of code in Python to implement the filter. Bilateral filter can be slow and it is not efficient at removing salt and pepper noise. References: https://people.csail.mit.edu/sparis/bf_course/course_notes.pdf cv2.cv2.bilateralFilter - https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_filtering/py_filtering.html skimage bilateral - https://scikit-image.org/docs/dev/auto_examples/filters/plot_denoise.html Code associated with these tutorials can be downloaded from here: https://github.com/bnsreenu/python_for_image_processing_APEER