Introduction: An efficient method of tomographic imaging in nuclear medicine is positron emission tomography (PET). Compared to SPECT, PET has the advantages of higher levels of sensitivity, spatial resolution and more accurate quantification. However, high noise levels in the image limit its diagnostic utility. Noise removal in nuclear medicine is traditionally based on Fourier decomposition o...

Image de-noising is a vital concern in image processing. Out of different available method wavelet thresolding method is one of the important approaches for image de-noises. In this paper we propose an adaptive method of image de-noising in the wavelet sub-band domain assuming the images to be contaminated with noise based on threshold estimation for each sub-band. Under this framework the prop...

In this paper a comparison between face recognition rate with noise and face recognition rate without noise is presented. In our work we assume that all the images in the ORL faces database are noisy images. We applied the wavelet based image de-noising methods to this database and created new databases, then the face recognition rate are calculated to them. Three experiments are given in our p...

The main challenge in de-noising by kernel Principal Component Analysis (PCA) is the mapping of de-noised feature space points back into input space, also referred to as “the pre-image problem”. Since the feature space mapping is typically not bijective, preimage estimation is inherently illposed. As a consequence the most widely used estimation schemes lack stability. A common way to stabilize...

Magnetic resonance imaging (MRI) is a principal modality of modern medical imaging, which provides a wide spectrum of useful diagnostic contrasts, both anatomical and functional in nature. Like many alternative imaging modalities, however, some specific realizations of MRI offer a trade-off in terms of acquisition time, spatial/temporal resolution and signal-to-noise ratio (SNR). Thus, for inst...

With the growth of the multimedia technology over the past decades, the demand for digital information has increased dramatically. This enormous demand poses difficulties for the current technology to handle. One approach to overcome this problem is to compress the information by removing the redundancies present in it. This is the lossy compression scheme that is often used to compress informa...

Received Jul 8, 2017 Revised Nov 20, 2017 Accepted Dec 11, 2017 This paper presents a novel audio de-noising scheme in a given speech signal. The recovery of original from the communication channel without any noise is a difficult task. Many de-noising techniques have been proposed for the removal of noises from a digital signal. In this paper, an audio denoising technique based on Short Time F...

Color image normally contain of three main colors at the each pixel, but the digital cameras capture only one color at each pixel using color filter array (CFA). While through capturing in color image, some noise/artifacts is added. So, the both demosaicing and de-noising are the first essential task in digital camera. Here, both the technique can be solve sequentially and independently. A conv...

The images usually bring different kinds of noise in the process of receiving, coding and transmission. In this paper the Curvelet transform is used for de-noising of image. Two digital implementations of the Curvelet transform (a multiscale transform) viz the Unequally Spaced Fast Fourier Transform (USFFT) and the Wrapping Algorithm are used to de-noise images degraded by different types of no...

Analysis and interpretation of 2D gel images is a very important task in proteonomics study. The nonlinearties in the gel formation and image acquisition process leads to distortions, overlapped protein spots, saturated spots, faint spots, nonlinear intensity and uneven background in the gel images. As a result, pre-processing steps are important before image-analysis. De-noising is one of the ...