![Displaying Images
>> g = imread('xray.tif');
>> imshow(g)
>> imshow(g, [10 100])
>> imshow(g, [ ])](https://image.slidesharecdn.com/diplec1-240802185934-ed6fdcb4/85/DIP-LEC-1-pptxlllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll-13-320.jpg)
DIP LEC 1.pptxlllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll
- 2. Fundamentals of Computer Imaging & Matlab (Matrix Laboratory) Gonzalez R. C., Woods R. E., Eddins S. L., Digital Image Processing Using Matlab, Pearson Education, 2nd edition, 2009. (Ch. 1)
- 3. Digital image processing is a field that focuses on manipulating and analyzing digital images using various algorithms and techniques. Digital image processing is the use of algorithms and mathematical models to process and analyze digital images. The goal of digital image processing is to enhance the quality of images, extract meaningful information from images, and automate image-based tasks.
- 4. Digital Image An image may be defined as a two-dimensional function, f(x, y), where x and y are spatial (plane) coordinates, and the amplitude of f at any pair of coordinates (x, y) is called the intensity or gray level of the image at that point.
- 5. Types of an image 1.BINARY IMAGE– The binary image as its name suggests, contain only two pixel elements i.e 0 & 1,where 0 refers to black and 1 refers to white. This image is also known as Monochrome. 2.BLACK AND WHITE IMAGE– The image which consist of only black and white color is called BLACK AND WHITE IMAGE.
- 6. Color images Color images can be modeled as three-band monochrome image data, where each band of data corresponds to a different color. The actual information stored in the digital image data is the gray-level information in each spectral band. Typical color images are represented as red, green, and blue (RGB images). Using the 8- bit monochrome standard as a model, the corresponding color image would have 24-bits/pixel (8-bits for each of the three color bands red, green, and blue). The figure below illustrates a representation of a typical RGB color image.
- 8. Image Formats Lossless compression Lossy compression Raster format Vector format 1. BMP (Microsoft Windows Bitmap) 2. GIF (Graphics Interchange Files) 3. HDF (Hierarchical Data Format) 4. JPEG (Joint Photographic Experts Group) 5. PCX (Paintbrush) 6. PNG (Portable Network Graphics) 7. TIFF (Tagged Image File Format) 8. XWD (X Window Dump)
- 9. The basic steps involved in digital image processing are: 1.Image acquisition: This involves capturing an image using a digital camera or scanner, or importing an existing image into a computer. 2.Image enhancement: This involves improving the visual quality of an image, such as increasing contrast, reducing noise, and removing artifacts. 3.Image restoration: This involves removing degradation from an image, such as blurring, noise, and distortion. 4.Image segmentation: This involves dividing an image into regions or segments, each of which corresponds to a specific object or feature in the image. 5.Image representation and description: This involves representing an image in a way that can be analyzed and manipulated by a computer, and describing the features of an image in a compact and meaningful way. 6.Image analysis: This involves using algorithms and mathematical models to extract information from an image, such as recognizing objects, detecting patterns, and quantifying features. 7.Image synthesis and compression: This involves generating new images or compressing existing images to reduce storage and transmission requirements.
- 11. Image processing mainly include the following steps: 1.Importing the image via image acquisition tools; 2.Analysing and manipulating the image; 3.Output in which result can be altered image or a report which is based on analysing that image.
- 12. Displaying Images >> f = imread('rose.tif'); >> imshow(f) >> g = imread('xray.tif'); >> figure, imshow(g) >> imshow(f), figure, imshow(g) >> doc imshow >> whos >> save habib >> clc >> clear all >> load habib File -> Set path: Select path where images are available
- 13. Displaying Images >> g = imread('xray.tif'); >> imshow(g) >> imshow(g, [10 100]) >> imshow(g, [ ])
Editor's Notes
- #8: PS and EPS are not necessarily vector format
- #13: imshow(I,[low high]) displays the grayscale image I, specifying the display range for I in [low high]. The value low (and any value less than low) displays as black; the value high (and any value greater than high) displays as white. Values in between are displayed as intermediate shades of gray, using the default number of gray levels. If you use an empty matrix ([]) for [low high], imshow uses [min(I(:)) max(I(:))]; that is, the minimum value in I is displayed as black, and the maximum value is displayed as white.