Image Processing Lecture Notes PDF

# Image Processing ## by ## DR\ Reham Amin ## [email protected] ### Author: Dr. Reham Amin - What do you expect to learn from this course? - **Outline** - Course Textbook - Course Links - Course Contents - What is an image? - Types of images - What is a digital ima...

# Image Processing ## by ## DR\ Reham Amin ## [email protected] ### Author: Dr. Reham Amin - What do you expect to learn from this course? - **Outline** - Course Textbook - Course Links - Course Contents - What is an image? - Types of images - What is a digital image? - How to obtain a digital image? - What is image processing? - Phases of Image Processing ### Course Text book - Digital Image Processing Using MATLAB, 3rd edition - Rafael Gonzalez, Richard Woods - Digital Image Processing Global Edition - 4th edition - Publication year: 2017 - Print-ISBN: 978-1-292-22304-9 - E-ISBN: 978-1-292-22307-0 - Pages: 1024 ### Author: Dr. Reham Amin - An image of two dogs side by side. - **What you see** - An arrow points to right. - **What computers see** | 255 | 255 | 218 | 94 | 107 | 127 | |---|---|---|---|---|---| | 251 | 11 | 10 | 93 | 98 | 120 | | 242 | 13 | 11 | 00 | 87 | 82 | | 19 | | | 81 | 78 | 74 | | | | | 47| 59 | 65 | | | | | 67 | 77 | 88 | | 180 | | | 82 | 103 | 137 | | 219 | | | 68 | | | | 230 | 59 | 58 | 57 | | | | 60 | 54 | 49 | 52 | 74 | 86 | | 69 | 60 | 46 | 54 | 77 | 83 | | | 78 | 74 | 81 | 93 | 101 | | | | | | 97 | | ### Author: Dr. Reham Amin - **What is an image?** - **A two-dimensional function**: representing a measure of some characteristic, such as brightness or color of a viewed scene. - **A projection**: of a 3-D scene into a 2D projection plane. - **A two-dimensional function f(m,n)**: - where **m and n** are spatial (plane) coordinates (row and column values), - and the **amplitude of f** at any pair of coordinates (m,n) is called the intensity of the image at that point. - **Pixel values**: are gray levels in range 0-255 or RGB colors ### Author: Dr. Reham Amin - **Types of images** - Binary image - Grayscale (8 bit) image - RGB Color image - RGBA Image ### Author: Dr. Reham Amin - **Binary Image** ### Author: Dr. Reham Amin - **Grayscale (8-bit) images** - Histogram of all RGB Colors - Histogram of Grayscale image ### Author: Dr. Reham Amin - **The effect of different number of intensity levels** ### Author: Dr. Reham Amin - **The effect of different intensity levels** - 256 Intensity Levels left vs 32 Intensity Levels right - Let's reduce the number of intensity values on the right image. ### Author: Dr. Reham Amin - **The effect of different intensity levels** - 256 Intensity Levels left vs 16 Intensity Levels right ### Author: Dr. Reham Amin - **The effect of different intensity levels** - 256 Intensity Levels left vs 8 Intensity Levels right ### Author: Dr. Reham Amin - **The effect of different intensity levels** - 256 Intensity Levels left vs 2 Intensity Levels right - **The image looks like a cartoon.** ### Author: Dr. Reham Amin - **RGB Color image** - Color images are formed by a **combination of individual 2-D images**. - (red, green and blue) **individual component images**. - **monochrome images** can be extended to color images by **processing the three component images individually**. - **different channels**: Like the gray-scale image, each channel is an image. - **row and column index**: In addition to accessing each image intensity with a row and column index, we also have an **index for each channel**, in this case, 0 for red, 1 for blue and 2 for green. - **continuous**: An image may be continuous with respect to the x- and y- coordinates and also in amplitude. Converting such an image to digital form requires that the coordinates, as well as the amplitude, be digitized. ### Author: Dr. Reham Amin - **RGB Color Image** - **16-bit matrices**: It is represented by a 16-bit matrices to computers. - **channels**: Three equal-sized matrices (called channels), each having values ranging from 0 to 255 - **matrix element**: Channels are stacked on top of each other, and thus we require three unique coordinates to specify the value of a matrix element. - **color**: Thus, a pixel in an RGB image will be of colour: - black when the pixel value is (0, 0, 0) - white when it is (255, 255, 255). - Red when it is (255, 0, 0) - Green when it is (0, 255, 0) - Blue when it is (0, 0, 255) ### Author: Dr. Reham Amin - **RGBA Image** - **extra channel**: RGBA images are colored RGB images with an extra channel known as "alpha" that depicts the opacity of the RGB image. - **0% to 100%**: Opacity ranges from a value of 0% to 100% and is essentially a "see-through" property. - **light**: Opacity in physics depicts the amount of light that passes through an object. - **cellophane**: For instance, cellophane paper is transparent (100% opacity), frosted glass is translucent, and wood is opaque. - **mimic**: The alpha channel in RGBA images tries to mimic this property. ### Author: Dr. Reham Amin - **So what is a DIGITAL IMAGE???** ### Author: Dr. Reham Amin - **WHAT IS A DIGITAL Image?** - **discrete pixels**: Digital image is a finite collection of discrete pixels of any observable object. - **finite range**: The pixels represent a two- or higher dimensional "view" of the object, each pixel having its own discrete value in a finite range. - **measurable value**: The pixel values may represent the amount of visible light, infra red light, absortation of x-rays, electrons, or any other measurable value such as ultrasound wave impulses. - **obtained**: The images may be obtained by a digital camera, scanner, electron microscope, ultrasound stethoscope, or any other optical or non-optical sensor. - **Examples of digital image are** - Digital photographs - Satellite images - Radiological images (x-rays, mammograms) - Binary images - Fax images - Engineering drawings ### Author: Dr. Reham Amin - **How to obtain a digital image?** ### Author: Dr. Reham Amin - **What is image processing?** - **digital computer**: The field of digital image processing refers to processing digital images by means of a digital computer - **better image**: The input is an image, and the output can be a better image or some important details from the image. - **important information**: Image processing involves performing operations on an image to make it better or to get important information from it. It's like fixing or improving a picture, and it's a bit like working with signals. - **attributes**: Digital image processing encompasses processes whose inputs and outputs are images and, in addition, includes processes that extract attributes from images up to, and including, the recognition of individual objects. - **automated analysis of text**: For example, consider the area of automated analysis of text. The processes of acquiring an image of the area containing the text, preprocessing that image, extracting (segmenting) the individual characters, describing the characters in a form suitable for computer processing, and recognizing those individual characters are in the scope of what we call digital image processing in this book. ### Author: Dr. Reham Amin - **Problem domain** - Color Image - Processing - Image - Restoration - Image - Filtering and - Enhancement - Image - Acquisition - **Knowledge base** - **Outputs of these processes generally are images** - Wavelets and - Other image - Transforms - Compression and - Watermarking - Morphological - Processing - Segmentation - Feature - Extraction - Image - Pattern - Classification - **Outputs of these processes generally are image attributes** ### https://www.v7labs.com/blog/image-processing-guide ### Author: Dr. Reham Amin - **Phases of Image Processing** ### https://www.v7labs.com/blog/image-processing-guidetphases of image-processing ### Author: Dr. Reham Amin - **Outputs of these steps are generally images** - Color Image - Processing - Image - Restoration - Image - Enhancement - Image - Acquisition - **Knowledge Base** - Wavelets & - Multiresolution - Processing - Compression - Morphological - Processing - Segmentation - Representation - & Description - Object - Recognition - **Outputs of these steps are generally images** - **Attributes** ### Author: Dr. Reham Amin - **Image Acquisition** ### Image Acquisition - **The image is captured by a camera and digitized** (if the camera output is not digitized automatically) using an analogue-to-digital converter for further processing in a computer. ### IMAGE ### ACQUISITION ### COMPONENTS ### Author: Dr. Reham Amin - **Image Enhancement** - **manipulated**: In this step, the acquired image is manipulated to meet the requirements of the specific task for which the image will be used. - **highlighting**: Such techniques are primarily aimed at highlighting the hidden or important details in an image, like contrast and brightness adjustment, etc. Image enhancement is highly subjective in nature. ### Author: Dr. Reham Amin - **Image Restoration** - **improving the appearance of an image**: This step deals with improving the appearance of an image and is an objective operation since the degradation of an image can be attributed to a mathematical or probabilistic model. For example, removing noise or blur from images. ### Author: Dr. Reham Amin - **Color Image Processing** - **colored images**: This step aims at handling the processing of colored images (16-bit RGB or RGBA images), for example, peforming color correction or color modeling in images. ### Author: Dr. Reham Amin - **Wavelets and Multi-Resolution Processing** - **building blocks**: Wavelets are the building blocks for representing images in various degrees of resolution. Images subdivision successively into smaller regions for data compression and for pyramidal representation. ### Author: Dr. Reham Amin - **Image Compression** - **COMPRESSION DONE PROPERLY: INVISIBLE TO THE NAKED-EYE** ### Author: Dr. Reham Amin - **Morphological Processing** - **useful in the representation and description of shape**: Image components that are useful in the representation and description of shape need to be extracted for further processing or downstream tasks. Morphological Processing provides the tools (which are essentially mathematical operations) to accomplish this. For example, erosion and dilation operations are used to sharpen and blur the edges of objects in an image, respectively. ### Author: Dr. Reham Amin - **Image Segmentation** - **partitioning an image into different key parts**: This step involves partitioning an image into different key parts to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation allows for computers to put attention on the more important parts of the image, discarding the rest, which enables automated systems to have improved performance. ### Author: Dr. Reham Amin - **Object Detection and Recognition** - **segmented from an image**: After the objects are segmented from an image and the representation and description phases are complete, the automated system needs to assign a label to the object-to let the human users know what object has been detected, for example, "vehicle" or "person", etc. ### Author: Dr. Reham Amin - **Knowledge Base** - **bounding box coordinates**: Knowledge may be as simple as the bounding box coordinates for an object of interest that has been found in the image, along with the object label assigned to it. Anything that will help in solving the problem for the specific task at hand can be encoded into the knowledge base. ### Author: Dr. Reham Amin - **Thank you**