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Advance Your Image Processing Knowledge
Read this to Advance Your Image Processing Knowledge
Today, automated image analysis has become an integral practice in multiple industrial and academic sectors. In order to analyze an image in detail, acquiring advanced image processing knowledge and skills can be highly useful.
Image processing as the name suggests is the process of editing images in a way to make them look more appealing and to identify the hidden details. Advanced image processing enhances the image in its best possible way. It is one of the most rapidly growing technologies used widely in medicine, forensic science, electrical engineering, and computer science domains.
Image processing can be carried out using two methods.
Due to the increase in the usage of digital mediums like digital cameras, computers, mobiles, etc., digital image processing method is used more often as compared to analogue image processing method. In order to understand image processing in detail let us look at the following steps.
1. Acquisition – The first step is to acquire the image from the source. It also includes aspects like scaling and color conversion. Color alteration enhances the image.
2. Image enhancement – This is a subjective phase, which may or may not be applicable for every image. However, this step exposes the hidden features of the image.
3. Image restoration – This step makes the image more appealing and may or may not be applicable for every image.
4. Color image processing – It deals with full color and pseudocolor image processing
5. Wavelets and Multiresolution processing – In this step, image is presented in various degrees for better image clarity.
6. Image compression – This step deals with image size and resolution modification.
7. Morphological processing – This step deals with extracting image components that can describe the shape of the objects in the image.
8. Segmentation Procedure – Segmentation is one of the most difficult steps of image processing. This step partitions the image into its constituent parts.
9. Representation & Description – This step transforms raw data into processed data
10. Object detection and recognition – In this step, one can assign labels to the objects detected after the entire image processing is completed.
Artificial Intelligence (AI) has proved to have several applications in image processing. For example, helping doctors in interpreting X-rays and MRI images by developing computer aided diagnosis systems. This is a breakthrough in medical sciences, making diagnosis simpler and easier to manage.
Image is simply a two-dimensional signal; however, image processing focuses on the details and hidden aspects of the image, enhancing its usability.
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