Skip to main content

Grey level thresholding. Level slicing. Contrast stretching lo p

Grey level thresholding.

Level slicing.

Contrast stretching.


Image enhancement


Lillesand and Kiefer (1994) explained the goal of image enhancement procedures is to improve the visual interpretability of any image by increasing the apparent distinction between the features in the scene. This objective is to create "new" image from the original image in order to increase the amount of information that can be visually interpreted from the data.


Enhancement operations are normally applied to image data after the appropriate restoration procedures have been performed. Noise removal, in particular, is an important precursor to most enhancements. In this study, typical image enhancement techniques are as follows:


Grey level thresholding


Grey level thresholding is a simple lookup table, which partitions the gray levels in an image into one or two categories - those below a user-selected threshold and those above. Thresholding is one of many methods for creating a binary mask for an image. Such masks are used to restrict subsequent processing to a particular region within an image.


This procedure is used to segment an input image into two classes: one for those pixels having values below an analyst- defined gray level and one for those above this value. (Lillesand and Kiefer, 1994).


Level slicing


Level slicing is an enhancement technique whereby the Digital Numbers (DN) distributed along the x-axis of an image histogram is divided into a series of analyst-specified intervals of "slices". All of DNs falling within a given interval in the input image are then displayed at a single DN in the output image (Lillesand and Kiefer, 1994).


Contrast stretching


Most satellites and airborne sensor were designed to accommodate a wide range of illumination conditions, from poorly lit arctic regions to high reflectance desert regions. Because of this, the pixel values in the majority of digital scenes occupy a relatively small portion of the possible range of image values. If the pixel values are displayed in their original form, only a small range of gray values will be used, resulting in a low contrast display on which similar features night is indistinguishable.


A contrast stretch enhancement expands the range of pixel values so that they are displayed over a fuller range of gray values. (PCI, 1997)


Generally, image display and recording devices typically operate over a range of 256 gray levels (the maximum number represent in 8-bit computer encoding). In the case of 8-bit single image, is to expand the narrow range of brightness values typically present in an output image over a wider range of gray value. The result is an output image that is designed to accentuate the contrast between features of interest to the image analyst (Lillesand and Kiefer, 1994).

The grey level or grey value indicates the brightness of a pixel. The minimum grey level is 0. The maximum grey level depends on the digitisation depth of the image. For an 8-bit-deep image it is 255. In a binary image a pixel can only take on either the value 0 or the value 255.



Comments

Popular posts from this blog

Kuhn’s Paradigms

The given content explains Thomas S. Kuhn’s model of scientific development , its application to geography, and criticisms by Karl Popper, Paul Feyerabend, Michel Foucault , and others. 1. Basic Idea Kuhn argued that science does not develop continuously in a straight line . Instead, scientific development occurs through: Preparadigm → Paradigm → Normal Science → Crisis → Scientific Revolution → New Paradigm A new paradigm may replace an older one, producing a major change in the way scientists understand and study a subject. Concepts and Terminologies Concept / Term Simple Meaning Paradigm A commonly accepted framework/model that guides scientific research Exemplar A successful concrete problem-solution used as a model for future research Disciplinary Matrix Shared beliefs, values, concepts, methods and techniques of a scientific community Preparadig...

Regional Geography, Systematic Geography, Idiographic, Nomothetic, Inductive and Deductive Approaches

T wo major ways of studying Geography : the Regional Approach and the Systematic Approach . It also explains the related ideas of idiographic vs. nomothetic and inductive vs. deductive reasoning , especially in the context of the Hartshorne–Schaefer debate . 1. Regional Geography: “All About One” Regional Geography studies one particular region in detail . A region is an area that has some degree of homogeneity (sameness) within its boundary but is also unique or different from other regions . For example, if we study Palakkad District , we may study: Relief and drainage Climate Soil Vegetation Agriculture Population Occupation Economy Culture Political characteristics The purpose is to understand the complete geographical personality of Palakkad and the relationships among its different features. Key concepts Region: A geographical area with identifiable characteristics and boundaries. Homogeneity: Si...

Models and Theories in Geography

Geographical Models A model is a simplified representation of reality used to describe, explain, simulate, and predict geographical phenomena. Types Physical (Iconic) Models – Three-dimensional representations (e.g., globe, relief model). Conceptual Models – Diagrams or frameworks explaining geographical relationships. Mathematical (Quantitative) Models – Equations and statistical models for spatial analysis and prediction. Simulation Models – Computer-based models that simulate geographical processes (e.g., climate, flood, urban growth). Major Geographical Models Model Scholar Year Concept Johann Heinrich von Thünen Agricultural Land Use Model 1826 Land use varies with distance from the market. Walter Christaller Central Place Model 1933 Distribution of settlements and services. Ernest Burgess Concentric Zone M...

Multispectral and Hyperspectral Imaging Systems

The main idea is how a remote-sensing sensor collects information about an area . A sensor does not simply take an ordinary photograph. It measures the electromagnetic energy reflected or emitted by objects in different wavelength bands . Depending on how many bands are measured and how the sensor collects them, different imaging systems are used. 1. Multispectral vs. Hyperspectral Multispectral imaging (MSI) records information in a limited number of relatively broad, separate spectral bands , such as blue, green, red, near-infrared and shortwave infrared. Hyperspectral imaging (HSI) records information in many narrow and usually contiguous spectral bands . Therefore, it provides a much more detailed spectral signature of each pixel. The resulting dataset is commonly called a hyperspectral data cube (hypercube) because it contains: X-axis → spatial information Y-axis → spatial information Z-axis → wavelength/spectral information Thus, hype...

Kuhn’s model in Geography

Thomas Kuhn (1922–1996) Thomas Samuel Kuhn was an American philosopher and historian of science . In 1962 , he published The Structure of Scientific Revolutions , introducing the concepts of paradigm and paradigm shift , which transformed the understanding of scientific progress. Definition: A framework of assumptions, concepts, and values that guide a group or field. Example (Science): Moving from a-earth-centered universe to a sun-centered solar system is a change in the scientific paradigm. Example (Daily Life): A shared cultural belief or a standard way of doing business.   Kuhn's Model (1962) Kuhn's Model explains that science develops through successive paradigms rather than by continuous, gradual progress. Stages of Kuhn's Model Pre-paradigm Stage – No common theory; different ideas exist. Normal Science – Scientists work within an accepted paradigm . Crisis – Anom...