A Review of Image Enhancement Techniques
Astha Kumari, M. Phil · 2015
Image Enhancement is one of the most important and difficult techniques in image research. The aim of image enhancement is to improve the visual appearance of an image, or to provide a better transform representation for future automated image processing. Many images like medical images, satellite images, aerial images and even real life photographs suffer from poor contrast and noise. It is necessary to enhance the contrast and remove the noise to increase image quality. One of the most important stages in medical images detection and analysis is Image Enhancement techniques which improves the quality (clarity) of images for human viewing, removing blurring and noise, increasing contrast, and revealing details are examples of enhancement operations. The enhancement technique differs from one field to another according to its objective. The existing techniques of image enhancement can be classified into two categories: Spatial Domain and Frequency domain enhancement. Thus the contribution of this paper is to classify and review image enhancement processing techniques. Image enhancement improves the interpretability or perception of information in images. For automated image processing system it provides better input. It helps scrutinize background information that is essential to understand object behavior without requiring manual inspection. Due to low contrast image enhancement becomes challenging and also objects cannot be extracted clearly from dark background. Images with object and background having similar color fail here. The existing techniques of image enhancement can be classified into two types: Spatial based domain image enhancement and Frequency based domain image enhancement. Spatial based domain image enhancement act on pixels directly. Frequency based domain image enhancement is a term used to describe the analysis of mathematical functions or signals with respect to frequency and operate directly on the image - transform coefficients. Commonly used transform co-efficient are Fourier Transform (FT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT). The basic idea is to enhance the image by manipulating the transform coefficients. Spatial domain methods can again be divided into two sections: Point Processing operation and spatial filter operations. Traditional image enhancement method enhances low quality image where the back ground information are lost in the darker region. In this case whatever technique we apply, information cannot be retrieved from darker back ground. Image Smoothing, Image Sharpening, filtering are some of the commonly used frequency domain enhancement techniques. In this paper we focus on both spatial and frequency image enhancement techniques.