Digital Image Processing

M. Venkata Dasu ¹, V. R. Anitha ², Fahimuddin Shaik ³, B. Abdul Rahim ⁴

Affiliations
1 Department of ECE, Annamacharya Institute of Technology & Sciences, Rajampet, Andhra Pradesh, IN
2 Department of ECE, Sri Vidya Nikethan Engineering College, Tirupathi, Andhra Pradesh, IN
3 Department of ECE, Annamacharya Institute of Technology & Sciences, Rajampet, Andhra Pradesh, IN
4 Department of ECE, Annamacharya Institute of Technology &sciences, Rajampet, Andhra Pradesh, IN

Abstract

Today we see rapid advancement in the field of Digital image processing and various enhancement techniques have been proposed for the extraction of details in color images. Decorrelation stretching is a method utilized to enhance the color component separation of an image with significant band-band correlation. It is also used as a data visualization tool for improving visual interpretation and make feature discrimination easier. It puts emphasis on high degree of scene variations. The net effect of the process is to obtain an output image whose pixels are well distributed among all possible colors, while preserving the relative sense of hue, saturation, and intensity. By performing linear contrast stretch on the obtained image will enhance the color ranges of the image. For further investigation, the color scatter plot of the image are obtained, which shows how the bands are decorrelated and equalized. The main objective of this paper is to obtain the color separation of images with the help of decorrelation stretching, linear contrast stretch and the color scatter plot of satellite images to investigate the area of vegetation, rock and water content.

Keywords

Decorrelation Stretching, Histogram, Karhunen-Loeve Transformation, Color Scatter Plot.

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J. Damodhar ¹, D. Sathyanarayana ², Fahimuddin Shaik ¹

Affiliations
1 Department of ECE, AITS, Rajampet, Andhra Pradesh, IN
2 Department of ECE, RGMEC, Nandyal, Andhra Pradesh, IN

Abstract

Lung cancer is one of the leading causes of death in the world. The early detection of cancer can be helpful in curing the disease completely. An early diagnosis of cancer can increase the chance of patient‟s survival from an average of 14% up to 49%. So the requirement of techniques to detect the occurrence of cancer nodule in early stage is increasing. There are different techniques existing but none of those provide better accuracy of detection. This paper provides a Computer Aided Diagnosis System (CAD) for early detection of lung cancer nodules from the Chest Computer Tomography (CT) images. This work represents a computer assisted diagnosis system of lung nodules with the help of two models, the extraction of lung parts can be achieved through the super imposition of input image with the lungs cropped image through Hand free cropping algorithm and then the enhancement of image is achieved by one of the contrast stretching techniques called CLAHE. The statistical values are calculated using MIPAV software.

Keywords

Lung Cancer, Computer Aided Diagnosis, Image Contract, CLAHE, Hand Free Cropping.

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V. Pani Kumar ¹, Fahimuddin Shaik ², M. N. Giri Prasad ³, B. Abdul Rahim ²

Affiliations
1 Department of ECE, AITS, Rajampet, IN
2 Department of ECE, AITS, Rajampet, Andhra Pradesh, IN
3 JNT University CE, Pulivendula, Andhra Pradesh, IN

Abstract

Acute leukemia is a type of cancer of the blood or bone marrow characterized by an abnormal increase of immature white blood cells or blasts play important role for hematologists in their diagnostic process. The acute leukemia is divided into acute lymphocytic leukemia (ALL) and acute myelogenous leukemia (AML), depending on whether specific white blood cells called lymphocytes (or myelocytes), are involved. Leukemia images from looking at a sample of patient blood, can determine the abnormal levels of white blood cells, to process a acute leukemia images so that the result is more suitable than the original image for a medical application. However, there are blurriness and effects of unwanted noise on blood leukemia images that sometimes result in false diagnosis. To over come this problem image pre-processing such as image enhancement techniques are needed. The results show that the global contrast stretching is the best technique that helps to improve the image quality.

Keywords

Image Enhancement, Contrast Stretching, Local Contrast, Global Contrast, Partial Contrast, Bright Contrast, Dark Contrast, Acute Leukemia.

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