Using digital algorithms to process digital images with the help of a digital computer is known as digital image processing. In simpler words, image processing is performing different operations upon images to enhance their quality. It is a set of processes under which the input is the image that you want to process to extract the information. And the output can be the features or characteristics that you wished to have developed. One of the rapidly growing technologies, digital image processing is gathering the interest of many students. Especially among the computer science and engineering graduates.
What steps do digital image processing applications include?
Image processing comprises three steps. Let’s know these three steps-
- Importing/Uploading the image using Image acquisition tools.
- First analyzing and then manipulating the image
- Receiving the output under which you can have the altered image or the extracted information. Whatever you should get.
What factors affect the generation and development of digital image processing?
Three factors affect the generation and development of digital image processing. Let’s know them-
- The development of digital computers
- The developments in mathematics, and,
- The high demand for applications in different economic and social sectors. Such as agriculture, environment, military, and medical sciences.
What is an image?
A two-dimensional surface captured by an optical device such as a camera is an image. A digital image comprises rows and columns specifically arranged in a two-dimensional array. Moreover, a digital image comprises finite elements. And each one of these elements has a particular value stored at a particular place. These elements are pixels, picture elements, and image elements. But, Pixels are the most common term used to denote the elements of a digital image. There are 4 different types of images. Let’s know these types in detail.
Binary Image
Also known as Monochrome, Binary Image comprises two-pixel elements only. These elements are 0 and 1. Here 0 is referring to black, and 1 refers to white.
Black & White Image
An Image made up of only two colors, black and white, is a black & white image.
8 Bit Color Format Image
A 256 colored image is an 8-Bit color format image. Also known as the grey-scale image, an 8-Bit color image is the most popular among all. Provided that 0 is for black, 127 is for grey, and 255 is for white.
16 Bit Color Format Image
With the most colors, the 16-Bit color format image offers more colors than the gray-scale format. Besides 65,536 colors, the 16-Bit color format image distributes colors differently than the popular 8-Bit color format. Also known as High Color Format, the 16-Bit Color Format is divided into three further formats. And these formats are the red, green, and blue formats. Thus known as the RGB Format.
What are Image Sensors?
An image sensor is an electronic device. Which converts optical images into electronic signals. Thus, used in digital cameras to reflecting the light falling upon the camera into the digital image.
What is Image Compression?
Simply saying, Image compression is reducing the byte size of images without reducing their quality. Helping in storing more digital images in less space. Also, it helps in reducing the time that an image takes to be uploaded over the internet. Or to be downloaded from it.
What are the different phases of digital image processing?
Digital image processing is a set of ten different phases. And, only after going through these 10 different phases, you can conclude an image as a digitally processed image. Let’s know the 10 different phases of digital image processing-
Image Acquiring
The process includes retrieving an image from a source. Here it may or may not be a hardware-based source. The first step includes the acquisition of an image. As without it, no further processing can be done. The image obtained is completely raw. Basically, under acquisition, scaling, and color conversion (Gray to RGB and vice versa) of an image is performed.
Image Enhancing
It includes making adjustments to digital images. Thus, the results become more suitable for displaying or analyzing purposes. Sharpening the image, brightening it, noise removal, and contrast adjustments are all parts of this phase. While enhancing an image, we modify the image to make it look more eye-pleasing.
Image Restoring
Recovering the degraded images because of different conditions is restoring images. The process is different from image enhancement and is completely objective.
Image Color Processing
The image color processing includes the processing of either RGB images or indexed images.
Multi-resolution and Wavelets Processing
Wavelets provide time-frequency information using small waves of limited durations. Which leads to multi-resolution processing. It includes the representation of images through various degrees of resolution.
Image Compressing
Compression is a unique technique that reduces the byte size of images without reducing their quality. It helps in saving some extra space on your hard disks and drives. Also, an image that is less or compressed is easy to upload and download. And takes very little time in the process than the actual image. Thus it is used to display images over the internet. A compressed image requires less amount of data. Making it easier to display an image from a server. Thus increasing the loading speed of the website.
Morphological Image Processing
It includes the extraction of components of an image. Helping in its representation and description of shape. Operations like dilation and erosion are parts of morphological image processing. And the output of it is image attributes.
Image Segmenting
Dividing a digital image into different segments is image segmenting. Its primary uses are locating images and developing image boundaries.
Image Representation and Description
Basically, under Image representation and description, we convert the image data into a suitable computer processing form. As it includes boundary representation and regional representation.
Boundary Representation
Boundary Representation focuses upon the external shape characteristics of an image. Thus, it includes borders and corners.
Regional Representation
Regional representation is the opposite of Boundary Representation. Because it focuses upon the internal characteristics of an image. Including the texture or quality of the image. It is also used as a differentiator of two classes.
Image Recognizing
It includes the last and the labeling phase of an image. Thus, naming the digital processed image comprises Image Recognition.
There is also a course for you if you want to enhance your knowledge or looking for certification in digital signal processing