There is an emerging trend to leverage noisy image datasets in many visual recognition tasks. However, the label noise among the datasets severely degenerates the performance of deep learning approaches. Recently, one mainstream is to introduce the latent label to handle label noise, which has shown promising improvement in the network designs. Nevertheless, the mismatch between latent labels a...

Proliferation of Digital Images across the internet has given rise to more systemise and effective image restoration methods. Process of image restoration involves procuring noise free original image from a corrupted noisy image. This process of image restoration is crucial in many areas such as satellite imaging, astronomical image & medical imaging where degraded images need to be repaired. T...

he image processing is the technology through which information of image get processed . the noises are the extra pixels which get added on the image to reduce image quality. The authors proposed various techniques which works to remove noisy pixels from the image. In this paper, various image de-nosing techniques has been reviewed and discuss in terms of their outcomes. KeywordsNoise, De-noisi...

We describe a variational framework for the tomographic reconstruction of an image from the maximum likelihood (ML) estimates of its orthogonal moments. We show how these estimated moments and their (correlated) error statistics can be computed directly, and in a linear fashion from given noisy and possibly sparse projection data. Moreover, thanks to the consistency properties of the Radon tran...

with the arrival of increasingly higher resolution pet systems, small amounts of motion can cause significant blurring in the images, compared to the intrinsic resolutions of the scanners. in this work, we have reviewed advanced correction methods for the three cases of (i) unwanted patient motion, as well as motions due to (ii) cardiac and (iii) respiratory cycles. for the first type of motion...

This thesis investigates the distributed information and detection of a binary source through a parallel system of relays. Each relay observes the source output through a noisy channel, and the channel outputs are independent conditional on the source input. The relays forward limited information through a noiseless link to the final destination which makes an optimal decision. The essence of t...

The inverse source problem for oneand two-dimensional coherently radiating sources is studied within the framework of generalized holographic imaging. It is shown that the image field produced from a generalized hologram of a one-dimensional source contains a complete description of the source. For such sources, structure larger than one-half wavelength is accurately imaged, whereas information...

The training of convolutional neural networks for image recognition usually requires large image datasets to produce favorable results. Those large datasets can be acquired by web crawlers that accumulate images based on keywords. Due to the nature of data in the web, these image sets display a broad variation of qualities across the contained items. In this work, a filtering approach for noisy...

Automatic Fingerprint Identification System (AFIS) uses fingerprint segmentation as its pre-processing step. A fingerprint segmentation step divides the fingerprint image into foreground and background. An AFIS that uses a feature extraction algorithm for person identification will tend to fail if it extracts spurious features from the noisy background area. So fingerprint image segmentation pl...

Beamlets are a special dyadically organized collection of line segments, exhibiting a range of lengths, positions and orientations. This collection is relatively compact: there are O(n log2(n)) beamlets, compared to O(n) line segments. This collection is relatively expressive: up to a certain tolerance, it does not take more than O(log2(n)) beamlets to approximate a single line segment. Because...