Quantization of a noisy source is a classic problem. Although, optimal solutions have been shown to exist under certain assumptions, they are usually either extremely difficult to implement or computationally very intensive. The vector quantization (VQ) based strategy we present in this paper is simple, efficient, and capable of joint compression and denoising of images corrupted by additive wh...

A new wavelet-based image compression scheme is proposed for use on noisy communications channels. In variable-length coding schemes, the occurrence of a single channel error can result in the entire image being lost. We adopt a simple approach based on error detection and recovery to stem the propagation of errors in the decoding process. Once the combined source/channel coding method is deene...

In this paper, a new noise reduction algorithm is proposed. In general, an edge—high frequency information in an image—would be filtered or suppressed after image smoothing. The noise would be attenuated, but the image would lose its sharp information. This defect makes the post-processing harder. One new algorithm performs connectivity analysis on edge-data to make sure that only isolated edge...

In this paper, we propose a Weakly Supervised Matrix Factorization (WSMF) approach to the problem of image parsing with noisy tags, i.e., segmenting noisily tagged images and then classifying the regions only with image-level labels. Instead of requiring clean but expensive pixel-level labels as strong supervision in the traditional image parsing methods, we take noisy image-level labels as wea...

We wish to recover an original image u from several blurrynoisy versions fk, called frames. We assume a more severe degradation model, in which the image u has been blurred by a noisy (stochastic) point spread function. We consider the problem of restoring the degraded image in a variational framework. Since the recovery of u from one single frame f is a highly ill-posed problem, we propose two...

The availability of labeled image datasets has been shown critical for high-level image understanding, which continuously drives the progress of feature designing and models developing. However, constructing labeled image datasets is laborious and monotonous. To eliminate manual annotation, in this work, we propose a novel image dataset construction framework by employing multiple textual metad...

In linear image restoration, the point spread function of the degrading system is assumed known even though this information is usually not available in real applications. As a result, both blur identification and image restoration must be performed from the observed noisy blurred image. This paper presents a computationally simple iterative blind image deconvolution method which is based on no...

Visual Cryptography comes under cryptography domain. It deals with encrypting and decrypting of visual information like pictures, texts, videos etc. Multi Secret Image Sharing (MSIS) scheme is a part of visual cryptography that provides a protected method to transmit more than one secret images over a communication channel. Conventionally, transmission of a single secret image is possible over ...

This research presents a new method of distinguishing between noisy, blurred and otherwise uncorrupted images via the Fourier transform. The spectrum of an image corrupted by noise is markedly different from one that is marred by blurring, or one that is not damaged at all. In particular, there are more high frequency terms in the spectrum of a noisy image than in that of a blurred image, and, ...

Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and t...