Let’s see how can we remove salt and pepper noise from the image by using Median filtering
What is Noise in the image ? Any real world sensor is affected by a certain degree of noise, whether it is thermal, electrical or otherwise. According to the wikipedia noise can be produced by the image sensor and circuitry of a scanner or digital camera. Image noise can also originate in film grain and in the unavoidable shot noise of an ideal photon detector. Image noise is an undesirable by-product of image capture that obscures the desired information. The original meaning of “noise” was “unwanted signal”; unwanted electrical fluctuations in signals received by AM radios caused audible acoustic noise (“static”). By analogy, unwanted electrical fluctuations are also called noise. Image noise can range from almost imperceptible specks on a digital photograph taken in good light, to optical and radio astronomical images that are almost entirely noise, from which a small amount of information can be derived by sophisticated processing. Such a noise level would be unacceptable in a photograph since it would be impossible even to determine the subject. There are different types of noises available.
This article is about the basic concepts behind a digital image, the processing of it, and hence, also the fundaments of CV. In the end, you can find a simple code implementation with Python using OpenCV. Understanding the Basics of Digital Image Processing and Computer Vision using OpenCV
In this article, a few image processing/computer vision problems and their solutions with python libraries (scikit-image, PIL, opencv-python) will be discussed. Some of the problems are from the exercises from this book (available on Amazon).
OpenCV is a huge open-source library for computer vision, machine learning, and image processing. OpenCV supports a wide variety of programming languages like Python, C++, Java, etc. OpenCV is one of the most popular computer vision libraries. If you want to start your journey in the field of computer vision, then a thorough understanding of the concepts of OpenCV is of paramount importance.
This tutorial is the foundation of computer vision delivered as “Lesson 2” of the series, there are more Lessons upcoming which would talk to the extend of building your own deep learning based computer vision projects.
The image processing library which stands for Open-Source Computer Vision Library was invented by intel in 1999 and written in C/C++