This paper presents a novel error detection and correction methodology for corrupted coefficients caused by transmission of coded images based on orthogonal transforms over a noisy channel. This method is based on the orthogonal property of image transforms, such as the discrete cosine transform. A few reference pixel intensities of each image block are replaced by a predetermined intensity lev...

Noisy image edge detection is one of the major areas of work in image processing. Edge detection of the noise-free images is much easier than finding the edge of noisy images. But in practice, many of the images are imbued with noise. This paper will present a new algorithm based on morphology operation to eliminate noise and perform correct edge detection simultaneously. The algorithm is appli...

The paper addresses a problem of tracking multiple number of frequencies using Regularized Autoregressive (RAR) approximation. The RAR procedure allows to decrease approximation bias, comparing to other AR-based frequency detection methods, while still providing competitive variance of sample estimates. We show that the RAR estimates of multiple periodicities are consistent in probabilit...

Error-correcting codes were first developed in the 1940s following a theorem of Claude Shannon [14] that showed that almost error-free communication could be obtained over a noisy channel. The message to be communicated is first “encoded”, i.e. turned into a codeword, by adding “redundancy”. The codeword is then sent through the channel and the received message is “decoded” by the receiver into...

In this paper we investigate the limits on optical detection of noisy watermarks that use a chaotic function, the logistic difference equation, in the watermark generation scheme. By varying the function seed, different chaotic sequences exhibiting lowpass and highpass characteristics, can be obtained for the same function, offering an added security advantage over watermarks generated using ps...