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Image Processing MR1510 Lecture 5. Image Processing Definition Image Processing is defined as the "examination, processing and analysis of (remotely sensed)

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Presentation on theme: "Image Processing MR1510 Lecture 5. Image Processing Definition Image Processing is defined as the "examination, processing and analysis of (remotely sensed)"— Presentation transcript:

1 Image Processing MR1510 Lecture 5

2 Image Processing Definition Image Processing is defined as the "examination, processing and analysis of (remotely sensed) images for the purpose of identifying objects and extracting information" Image analysts study remotely sensed data and use visual and computer-based processing techniques, tools and equipment to detect, identify, classify, measure and evaluate physical and cultural objects (the environment), their spatial patterns and relationships Data Information Pathway

3 Images are available in two forms - photographic film form and digital form. Aerial Photographs (oblique and vertical) – taken with a camera/film/filter combination are considered to be traditional forms of remotely sensed imagery – known as ANALOG format Analysed and Interpreted using Photo- interpretation (mirror and pocket stereoscopes) Variations in the scene characteristics are represented as variations in brightness on photographic films. A particular part of scene reflecting more energy will appear bright while a different part of the same scene that reflecting less energy will appear black. Today, most remotely sensed imagery (as opposed to photography) is recorded in a DIGITAL format for processing by desktop computers (PCs) to produce computer-based images for (online) interpretation purposes. Image Processing

4 Digital images consist of discrete picture elements called PIXELS. Associated with each pixel is a number represented as DN (Digital Number), that depicts the average radiance of relatively small area within a scene. The size of this area affects the reproduction of details within the scene. As the pixel size is reduced more scene detail is preserved in digital representation (spatial resolution). Image Processing DN PIXEL Matrix of Numbers

5 Analysis of remotely sensed data is undertaken using various image processing techniques and tools including: –Analog image processing. (traditional) –Digital image processing. (computer) Visual or Analog processing techniques are applied to hard copy data/and softcopy or on-screen such as photographs or printouts, computer displays. Image analysis in visual techniques adopts certain elements of interpretation, which are as follows: Tone, Texture, Colour, Shape, Size, Association…. The use of these fundamental elements depends not only on the area being studied, but the knowledge the analyst has of the study area. For example the texture of an object is also very useful in distinguishing objects that may appear the same if the judging solely on tone (i.e., water and a tree canopy, may have the same mean brightness values, but their texture is much different). Image Processing

6 Aerial Photography 9 (23cm) Altimeter (height) Fiducial Marks Documentation Bubble Level Mask Clock Film Type and Focal length of lens Principal Point (PP) Characteristics

7 Aerial Photography Stereoscopy Photo 1 Photo 2 60% overlap 40% gain Ground Sea level Stereocover (Geonex software – Photogrammetric Flight Planner) Stereoscopic viewing Pocket stereoscope Mirror stereoscope Stereoscopic pair Baselining Eyebase (distance between photo frames) Viewing 3D model Magnification – Exaggeration Aid to mapping Photogrammetry (quantitative measurements from photographs including heighting/contouring) 2D plane 3D world Height (topography) Aircraft Flightline

8 Association, for example, is a very powerful image analysis tool when combined with general knowledge (apriori) of the site. Collateral, Contextual or Ancillary data and personal knowledge of the task assist in image processing. The combination of examining remotely sensed data in the form of multispectral, multitemporal, multiscale imagery, in conjunction with multidisciplinary approaches provide us with a clue to identity of a feature Analog image processing techniques also include optical photogrammetric techniques (photgrammetry) allowing for precise measurement of the height, width, location, etc. of an object. Image Processing

9 Digital Image Processing is a collection of techniques for the manipulation of digital images by computers. Raw data received from sensors on the satellite platforms contains flaws and deficiencies. To overcome these flaws and deficiencies in order to get the original data several steps of processing are required. This varies from image to image depending on the type of image format, initial condition of the image and the information of interest and the composition of the image scene. Pre-processing Feature Extraction Display and enhancement Information extraction Digital Image Processing

10 Pre-processing prepares image data for subsequent analysis and attempts to correct or compensate for systematic errors present in all images. The digital images are corrected for geometry and atmospheric noise (amongst other things), These errors are systematic and can be removed before they reach the user. Digital Image Processing

11 Geometric Corrections Raw digital images often contain serious geometrical distortions that arise from Earth curvature, platform motion, relief displacement of the ground, scanning device. The distortions involved are of two types: –Non-systematic Distortion –Systematic Distortions Rectification is the process of projecting image data onto a plane or surface and making it conform to a map projection system. Registration is the process of making image data conform to another image. A map coordinate system is not necessarily involved. Rectification involves rearrangement of the input pixels onto a new grid which conforms to the desired map projection and coordinate system. Rectification and Registration therefore involve similar sets of procedures for both the distortions. Digital Image Processing

12 Atmospheric Corrections The output from the instrument on satellite (the image) depends on the intensity and spectral distribution of energy that is received at the satellite. The intensity and spectral distribution of energy/radiation travels through the atmosphere and accordingly suffers both attenuation (reduction) and augmentation (addition) in the course of journey. A problem for interpretation concerns not being able to regenerate the correct radiation properties of the target body (at the ground) on the Earths surface with the data generated by the remote sensing Restore image Digital Image Processing

13 Feature Extraction Statistical" characteristics of image data such as individual bands or a combination of band values that carry information concerning systematic variation within the scene. In a multi-spectral dataset it helps to portray the necessary elements of the image. It reduces the number of spectral bands that have to be analyzed. Finally it leads to increases in the speed of analysis and reduces the cost of analysis. Digital Image Processing

14 Image Enhancement Techniques Image Enhancement techniques are used to make satellite (as opposed to aerial photography) imagery more informative and to help achieve the goal of image interpretation. Enhancement means alteration of the appearance of an image in such a way that the information contained in that image is more readily interpreted visually in terms of a particular need. The image enhancement techniques are applied either to single-band images or separately to the individual bands of a multi-band image set. These techniques can be categorized into two: –Spectral Enhancement Techniques –Multi-Spectral Enhancement Techniques Digital Image Processing

15 Image Enhancement serves to improve the interpretability of the image by increasing apparent contrast among various features in the scene. The enhancement techniques depends upon two factors: –The digital data (i.e. with spectral bands and resolution) –The objectives of the interpretation As an image enhancement technique often drastically alters the original numeric data, it is normally used only for visual (manual) interpretation and not for further numeric analysis. Digital Image Processing

16 Image Enhancement Column (j) Row (i) Column (j) Row (i) MAT (i,j) - n x n FILTMAT (i,j) - 3 x 3 ? ? e.g. FILTERING

17 Information Extraction is the final step in image analysis. After pre-processing, feature extraction, and image enhancement the remotely sensed data is subjected to quantitative analysis to assign individual pixels to specific classes. Classification of the image is based on the known and unknown identity to classify the remainder of the image consisting of those pixels of unknown identity. After classification is complete, it is necessary to evaluate its accuracy by comparing the categories on the classified images with the areas of known identity on the ground (ground-truthing) The final result of the analysis consists of a map (or image) Digital Image Processing

18 Typical Examples of Digital Image Processing software: Erdas Imagine (UoA) – Geography folder Idrisi Kilimanjaro (UoA) – Geography folder Multispec (free download) PCI Geomatics ERMapper ENVI Pixoneer PGSteamer Also training package from UNESCO ….. BILKO

19 Digital Image Processing

20 BILKO EXERCISES (DULY COMPLETED) 1.Introduction to Digital Image Processing 2.Applications x 2 Read instructions. Introduction familiarises you with the software (BILKO) and the two applications allow you to carry out a couple of simple exercises using the software Available on the website Further details about BILKO at: Digital Image Processing

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