Image Processing

Image processing

Image processing involves performing some manipulations on an image. There are two types of image processing- analog and digital image processing.. The former consists of manipulating images used on hard surfaces example on printouts while the latter is the one which most of us are accustomed to. It is how you manipulate an image using Photoshop. Digital image processing has dominated the world to such an extent that only a few  use analog image manipulation. It has a wide range of applications. In higher-level learning institutions, the assignments involving image processing are common.

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Image

What is an image? The answer to this question is  subjective one and largely relies on  the field the respondent comes from. A person with a signal processing background can define it as a signal with two dimensions, while a person from geometry can define it as a set of points in a 3D or 2D space. In some cases, a video is considered a collection of images. In its simplest case, we can define an image as a visual representation of something.

Types of images

  1. Binary image.

It is a pixel image with two elements, 0 and 1, where 0 represents white and 1 black. Binary images are used for masking regions of interest in an image.

  1. Grayscale images.

They  have only a shade of gray color. They are the ones mostly used in image processing

  1. Colored images.

These types of digital images have color information for the pixels.

Image processing.

The process of image processing involves three steps. First, the image has to be imported to the processing software. Our image processing assignment experts are proficient in using major image processing software such as C++, Java, and Matlab.

After loading the image, the second step is analyzing or manipulating the image. This is where the bulk of image processing lies . Image processing derives its name from all manipulations that happen at this stage. In most cases, a computer quantifies an image as a continuous variable with x and y coordinates. The points are then converted to a matrix. Digital image processing involves manipulating these minute points. When all the manipulations and analyses are  done, the image is produced as an output. Due to the alterations that have been done to the image, it is always an improved version of the input image.

Image manipulations.

Our image processing assignment solutions will involve an image manipulated in the following ways.

  1. Image enhancement. An image is manipulated using heuristic approaches to improve its quality so that a user can extract useful information from it. Activities here could include sharpening the image, removing noise, and brightening the image. The objective is to make it easy to identify the key features of the image.
  2. Image restoration. This is the process of recovering a corrupt part of an image. Corruption in an image could be in the form of a camera miss-focus, blur, and noise. A rather complicated process is used which involves using mathematical algorithms to estimate the corrupt parts.

Applications of image processing.

  • Remote sensing
  • Color processing
  • Pattern recognition
  • Machine and robot vision
  • Medical field.

Matlab is well equipped with a toolbox for image processing, known as an image processing toolbox. With Matlab, you can do all the image manipulations. Our experts are highly proficient  in it. You should visit our platform when you need image processing using Matlab homework help. We are a legit online student assistance company that offers quality services to its clients. Experts who have honed their experience over time in Matlab provide you the image processing assignment solutions.