INTRODUCTION TO IMAGE PROCESSING - drkmm.com

1 Readings in IMAGE PROCESSING OVERVIEW OF IMAGE PROCESSING . Rao*,Deputy Director,NRSA,Hyderabad-500 037. INTRODUCTION IMAGE PROCESSING is a technique to enhance Methods of IMAGE PROCESSING raw images received from cameras/sensors There are two methods available in IMAGE placed on satellites, space probes and PROCESSING . aircrafts or pictures taken in normal day-to- day life for various applications. Analog IMAGE PROCESSING Various techniques have been developed in Analog IMAGE PROCESSING refers to the IMAGE PROCESSING during the last four to five alteration of IMAGE through electrical means. decades. Most of the techniques are The most common example is the television developed for enhancing images obtained IMAGE . from unmanned spacecrafts, space probes and military reconnaissance flights.

2 IMAGE The television signal is a voltage level which PROCESSING systems are becoming popular varies in amplitude to represent brightness due to easy availability of powerful personnel through the IMAGE . By electrically varying the computers, large size memory devices, signal, the displayed IMAGE appearance is graphics softwares etc. altered. The brightness and contrast controls on a TV set serve to adjust the amplitude and IMAGE PROCESSING is used in various reference of the video signal, resulting in the applications such as: brightening, darkening and alteration of the brightness range of the displayed IMAGE . Remote Sensing Medical Imaging Digital IMAGE PROCESSING Non-destructive Evaluation Forensic Studies In this case, digital computers are used to Textiles process the IMAGE .

3 The IMAGE will be Material Science. converted to digital form using a scanner . Military digitizer [6] (as shown in Figure 1) and then Film industry process it. It is defined as the subjecting Document PROCESSING numerical representations of objects to a Graphic arts series of operations in order to obtain a Printing Industry desired result. It starts with one IMAGE and produces a modified version of the same. It is The common steps in IMAGE PROCESSING are therefore a process that takes an IMAGE into IMAGE scanning, storing, enhancing and another. interpretation. The schematic diagram of IMAGE scanner-digitizer diagram is shown in The term digital IMAGE PROCESSING generally figure 1. refers to PROCESSING of a two-dimensional picture by a digital computer [7,11]. In a broader context, it implies digital PROCESSING of any two-dimensional data.

4 A digital IMAGE is an array of real numbers represented by a finite number of bits. The principle advantage of Digital IMAGE PROCESSING methods is its versatility, repeatability and the preservation of original Figure 1 data precision. * Deputy Director, National Remote Sensing Agency, Hyderabad, India. e-mail: 1. Readings in IMAGE PROCESSING The various IMAGE PROCESSING techniques IMAGE Preprocessing are: Scaling IMAGE representation IMAGE preprocessing The theme of the technique of magnification is IMAGE enhancement to have a closer view by magnifying or IMAGE restoration zooming the interested part in the imagery. IMAGE analysis By reduction, we can bring the unmanageable IMAGE reconstruction size of data to a manageable limit. For IMAGE data compression resampling an IMAGE Nearest Neighborhood, Linear, or cubic convolution techniques [5] are IMAGE Representation used.

5 An IMAGE defined in the "real world" is I. Magnification considered to be a function of two real variables, for example, f(x,y) with f as the This is usually done to improve the scale of amplitude ( brightness) of the IMAGE at the display for visual interpretation or sometimes real coordinate position (x,y). The effect of to match the scale of one IMAGE to another. digitization is shown in Figure 2. To magnify an IMAGE by a factor of 2, each pixel of the original IMAGE is replaced by a block of 2x2 pixels, all with the same brightness value as the original pixel. Figure 2. The 2D continuous IMAGE f(x,y) is divided into N rows and M columns. The intersection of a row and a column is called as pixel. The value assigned to the Figure 3 IMAGE Magnification integer coordinates [m,n] with {m=0,1, 2.}

6 ,M-1} and {n=0,1,2,..,N-1} is f[m,n]. In II. Reduction fact, in most cases f(x,y)--which we might consider to be the physical signal that To reduce a digital IMAGE to the original data, impinges on the face of a sensor. every mth row and mth column of the original Typically an IMAGE file such as BMP, imagery is selected and displayed. Another JPEG, TIFF etc., has some header and way of accomplishing the same is by taking picture information. A header usually the average in 'm x m' block and displaying includes details like format identifier this average after proper rounding of the (typically first information), resolution, resultant value. number of bits/pixel, compression type, etc. 2. Readings in IMAGE PROCESSING Mosaic Mosaic is a process of combining two or more images to form a single large IMAGE without radiometric imbalance.

7 Mosaic is required to get the synoptic view of the entire area, otherwise capture as small images. Figure 4 IMAGE Reduction Rotation Rotation is used in IMAGE mosaic, IMAGE registration etc. One of the techniques of rotation is 3-pass shear rotation, where rotation matrix can be decomposed into three separable matrices. 3-pass shear rotation R = | cos sin | =. | sin cos |. | 1 tan /2 | | 1 0| | 1 tan /2|. |0 1 | | sin 1| |0 1 | Figure 6 IMAGE Mosaicking IMAGE Enhancement Techniques Some times images obtained from satellites and conventional and digital cameras lack in contrast and brightness because of the limitations of imaging sub systems and illumination conditions while capturing IMAGE . Images may have different types of noise. In IMAGE enhancement, the goal is to accentuate certain IMAGE features for subsequent analysis or for IMAGE display[1,2].

8 Examples include contrast and edge enhancement, pseudo-coloring, noise filtering, sharpening, and magnifying. IMAGE enhancement is useful in feature extraction, IMAGE analysis and an IMAGE display. The enhancement process itself does not increase the inherent Figure 5 3-Pass Shear Rotation information content in the data. It simply emphasizes certain specified IMAGE Advantages characteristics. Enhancement algorithms are 1. No scaling no associated resampling generally interactive and application- degradations. dependent. 2. Shear can be implemented very efficiently. 3. Readings in IMAGE PROCESSING Some of the enhancement techniques are: Contrast Stretching Noise Filtering Histogram modification Contrast Stretching: Some images (eg. over water bodies, deserts, dense forests, snow, clouds and under hazy conditions over heterogeneous regions) are Figure 8 Noise Removal homogeneous , they do not have much change in their levels.

9 In terms of histogram representation, they are characterized as the occurrence of very narrow peaks. The homogeneity can also be due to the incorrect illumination of the scene. Ultimately the images hence obtained are not easily interpretable due to poor human perceptibility. This is because there exists only a narrow range of gray-levels in the Figure 9 Edge Enhancemen IMAGE having provision for wider range of gray-levels. The contrast stretching methods Histogram Modification are designed exclusively for frequently encountered situations. Different stretching Histogram has a lot of importance in IMAGE techniques have been developed to stretch enhancement. It reflects the characteristics of the narrow range to the whole of the available IMAGE . By modifying the histogram, IMAGE dynamic range.

10 Characteristics can be modified. One such example is Histogram Equalization. Histogram equalization is a nonlinear stretch that redistributes pixel values so that there is approximately the same number of pixels with each value within a range. The result approximates a flat histogram. Therefore, Figure 7 contrast stretching contrast is increased at the peaks and lessened at the tails. Noise Filtering Noise filtering is used to filter the unnecessary information from an IMAGE . It is also used to remove various types of noises from the images. Mostly this feature is interactive. Various filters like low pass, high pass, mean, median etc., are available. Figure 10 Histogram equalized output 4. Readings in IMAGE PROCESSING IMAGE Analysis are in good registration. Most of the information extraction techniques rely on IMAGE analysis is concerned with making analysis of the spectral reflectance properties quantitative measurements from an IMAGE to of such imagery and employ special produce a description of it [8].