Image Processing 101: Spatial Filters (Convolution)

This article is part of our Image Processing 101 blog series. In the last post, we discussed gamma transformation, histogram equalization, and other image enhancement techniques. The commonality of these methods is that the transformation is directly related to the pixel gray value, independent of the neighborhood in which the pixel is located. In this post, we…

Image Processing 101: Point Operations

This article is part of our Image Processing 101 blog series. Spatial domain image enhancement techniques can be divided into two broad categories: Point operations Neighborhood operations This post discusses the point operations and the next post will be covering the neighborhood operations. Point operations refer to running the same conversion operation for each pixel in a…

Image Processing 101: Image Enhancement

What is Image Enhancement? This article is part of our Image Processing 101 blog series. Image enhancement refers to the process of highlighting certain information of an image, as well as weakening or removing any unnecessary information according to specific needs. For example, eliminating noise, revealing blurred details, and adjusting levels to highlight features of an image….

Image Processing 101: Color Space Conversion

color image of a mobile device reading barcodes on a craft box

This article is part of our Image Processing 101 blog series. In the last post, we discussed a few common color models, specifically RGB, HSV, and YUV. A color model is an abstract mathematical model that describes how colors can be represented as a set of numbers. In this post, we will look at how to convert…

Image Processing 101: Color Models

This article is part of our Image Processing 101 blog series. What is a Color Model? A color model is an abstract mathematical model that describes how colors can be represented as a set of numbers (e.g., a triple in RGB or a quad in CMYK). Color models can usually be described using a coordinate system, and…

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