Homomorphic Filtering Technique Research Articles

The main objective of the image enhancement is to improve the visual appearance or quality of an image. In this paper, the proposed scheme aims to improve the performance of the homomorphic filtering by employing the fractional derivatives with Discrete Fourier Transform (DFT) and Fractional Fourier Transform (FrFT). FrFT in combination with fractional derivative provides two fractional orders as extra degrees of freedom, thus, providing more design flexibility. This paper uses Grunwald-Letnikov (GL) fractional derivative to enhance the high and mid frequency components non-linearly while preserving the low frequency components. In the proposed approach, modification of homomorphic filtering technique is done on the basis of fractional derivative and FrFT to enhance the low contrast and non-uniformly illuminated images. The effectiveness of the proposed work is evaluated on the basis of various image assessment parameters such as PSNR, information entropy, universal image quality index, etc. on several images of different sizes. The proposed scheme outperforms the existing state-of-the-art techniques by providing better image visual quality and image information in terms of average PSNR and entropy values. The improvement in the average PSNR and information entropy is in the range 0.2635–50.37 dB and 0.02–42% respectively for standard images as well as for images with different contrast and illumination conditions.

Speckle noise is the universal distortion problem in synthetic aperture radar (SAR) images. Despeckling method resolves this problem. This article presents an improved and enhanced homomorphic filtering technique using wiener filter to avoid blurring and to increase the computational time of execution. The proposed method is enhanced by applying log transform after the discrete wavelet transform (DWT) only at the detailed part. This saves the overall time of computational process and the results are also satisfactory and easily acceptable. This scheme is proposed in db2 type wavelet transform. Wiener filter is applied on the approximate part. The performance of the scheme is evaluated by calculating PSNR, SSIM and computational time. The performance of the resulting improved homomorphic filtering technique is compared with some standard methods and filters, and it shows better results in terms of numerical and visual comparison. Keywords: homomorphic filtering; dwt; wiener filter; speckle noise; SAR image

Although a face image can be described in illumination-reflectance model, the illumination and reflectance components are not distinctly separated in the frequency domain after the Fourier transformation. In fact, the illumination components of a poorly illuminated face image can be divided into two regions, namely low frequency region and vertical center region. This paper proposed two methods to identify the locations of illumination component in the face images which consist of different subjects and illumination directions. By using inspection method and mean square error (MSE) function, the illumination locations can be determined accurately. The largest location of illumination component discovered via the research will be used as reference parameters to design a customized filter before it is implemented in homomorphic filtering technique.

Variable illumination in a texture is a common problem occurs to a real-time image modalities. The imbalance illumination in a texture creates virtual regions within one image, hence it affects the performance of the classification methods because it introduced an artifact patterns or virtual regions to an image. This paper presents a method to overcome the variable illumination problem in a pig skin texture using the information in the local and global blocks. The focus of this paper is to provide a fast, reliable and safe method to stabilize the lighting in an image. Pig skin texture is selected because it has a special pattern characteristic that needs to be preserved. The results show that in terms of the fluctuations contrast amplitudes in an image, the local-global method give better results than the standard homomorphic filtering technique.