Image enhancement is a processing on an image in order to make it more appropriate for certain applications. It is used to improve the visual effects and the clarity of image or to make the original image more conducive for computer to process. In this paper we are going to review the different image contrast enhancement techniques. Image Enhancement techniques increase the contrast of image wh...

The paper presents speech enhancement scheme for suppression of different background noises. The objective of speech enhancement is to improve the quality of the processed speech. This paper also investigate the use of two different transforms for speech enhancement. Speech enhancement using wiener filtering approach is presented using transforms DFT and DCT. The type of transform shows differe...

Fingerprint image enhancement is a common and critical step in fingerprint recognition systems. To enhance the images, most of the existing enhancement algorithms use filtering techniques that can be categorized into isotropic and anisotropic according to the filter kernel. Isotropic filtering can properly preserve features on the input images but can hardly improve the quality of the images. O...

In this paper we introduce a new class of nonlinear filters called Median-Rational Hybrid Filters (MRHF) based on Rational Functions (RF). The filter output is the result of a rational operation taking into account three sub-functions, such as two FIR or median subfilters and one center weighted median filter (CWMF). The proposed MRHF filters have the inherent property that on smooth areas they...

Two kinds of wavelet features are proposed: (a) Kirsch edge enhancement based 2D wavelets and (b) 2D complex wavelets. The two sets of hybrid features are congregated by combining them with the geometrical features for the recognition of handwritten numerals. Experiments conducted on handwritten numeral recognition and verification show that the two hybrid feature sets can achieve high recognit...

We introduce EnhanceGAN, an adversarial learning based model that performs automatic image enhancement. Traditional image enhancement frameworks involve training separate models for automatic cropping or color enhancement in a fully-supervised manner, which requires expensive annotations in the form of image pairs. In contrast to these approaches, our proposed EnhanceGAN only requires weak supe...

Technical limitations in image capturing usually impose defective, such as contrast degradation. There are different approaches to improve the contrast of an image. Among the exiting approaches, un-sharp masking is a popular method due to its simplicity in implementation and computation. There is an important parameter in un-sharp masking, named gain factor, which affects the quality of the enh...