This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.

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Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

A new decision-based algorithm is proposed for restoration of images that are highly corrupted by impulse noise. The new algorithm shows significantly better image quality than a standard median filter (SMF), adaptive median filters (AMF), a threshold decomposition filter (TDF), cascade, and recursive nonlinear filters. The proposed method, unlike other nonlinear filters, removes only corrupted pixel by the median value or by its neighboring pixel value. As a result of this, the proposed method removes the noise effectively even at noise level as high as 90% and preserves the edges without any loss up to 80% of noise level. The proposed algorithm (PA) is tested on different images and is found to produce better results in terms of the qualitative and quantitative measures of the image

A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises

A novel switching median filter incorporating with a powerful impulse noise detection method, called the boundary discriminative noise detection (BDND), is proposed in this paper for effectively denoising extremely corrupted images. To determine whether the current pixel is corrupted, the proposed BDND algorithm first classifies the pixels of a localized window, centering on the current pixel, into three groups-lower intensity impulse noise, uncorrupted pixels, and higher intensity impulse noise. The center pixel will then be considered as "uncorrupted," provided that it belongs to the "uncorrupted" pixel group, or "corrupted." For that, two boundaries that discriminate these three groups require to be accurately determined for yielding a very high noise detection accuracy-in our case, achieving zero miss-detection rate while maintaining a fairly low false-alarm rate, even up to 70% noise corruption. Four noise models are considered for performance evaluation. Extensive simulation results conducted on both monochrome and color images under a wide range (from 10% to 90%) of noise corruption clearly show that our proposed switching median filter substantially outperforms all existing median-based filters, in terms of suppressing impulse noise while preserving image details, and yet, the proposed BDND is algorithmically simple, suitable for real-time implementation and application.

A switching median filter with boundary discriminative noise detection for extremely corrupted images

A modified decision based unsymmetrical trimmed median filter algorithm for the restoration of gray scale, and color images that are highly corrupted by salt and pepper noise is proposed in this paper. The proposed algorithm replaces the noisy pixel by trimmed median value when other pixel values, 0's and 255's are present in the selected window and when all the pixel values are 0's and 255's then the noise pixel is replaced by mean value of all the elements present in the selected window. This proposed algorithm shows better results than the Standard Median Filter (MF), Decision Based Algorithm (DBA), Modified Decision Based Algorithm (MDBA), and Progressive Switched Median Filter (PSMF). The proposed algorithm is tested against different grayscale and color images and it gives better Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF).

Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter

The known median-based denoising methods tend to work well for restoring the images corrupted by random-valued impulse noise with low noise level but poorly for highly corrupted images. This letter proposes a new impulse detector, which is based on the differences between the current pixel and its neighbors aligned with four main directions. Then, we combine it with the weighted median filter to get a new directional weighted median (DWM) filter. Extensive simulations show that the proposed filter not only can provide better performance of suppressing impulse with high noise level but can preserve more detail features, even thin lines. As extended to restoring corrupted color images, this filter also performs very well

A New Directional Weighted Median Filter for Removal of Random-Valued Impulse Noise

A new impulse noise detection technique for switching median filters is presented, which is based on the minimum absolute value of four convolutions obtained using one-dimensional Laplacian operators. Extensive simulations show that the proposed filter provides better performance than many of the existing switching median filters with comparable computational complexity. In particular, the proposed filter is directed toward improved line preservation.

A new impulse detector for switching median filters

A new encryption technique is proposed to encrypt color images using existing optical encryption systems for gray-scale images. The color images are converted to their indexed image formats before they are encoded. At the decryption end, the color images are recovered by converting the decrypted indexed images back to their RGB formats. The proposed single-channel color image encryption method is more compact and robust than the multichannels methods. Since color information is added to the shape information, better verification performance can be achieved in optical security systems. ©1999 John Wiley & Sons, Inc. Microwave Opt Technol Lett 21: 318–323, 1999.

Color image encryption using double random phase encoding

The performance of nonlinear morphological correlation is investigated and compared with that of conventional linear correlation. In particular, the effects of illumination variations on the morphological correlation output are investigated in detail. The morphological correlation is shown to be invariant to uniform input-image illumination when the input-image illumination is higher than that of the reference. It also provides higher pattern discriminability, sharper peaks, and more-robust detection in the presence of salt-and-pepper noise than does the linear correlation. Computer-simulation results are provided.

Illumination-invariant pattern recognition with joint-transform-correlator-based morphological correlation

We propose a new optical stream cipher for security applica- tions. The stream cipher's security is enhanced using hybrid cellular au- tomata to replace uniform cellular automata as the keystream genera- tors. The encoded ciphertext is obtained by randomly encoding both the initial states of cellular automata and their evolution rules. This results in an increase in complexity to crack the keystream generator and, thus, enhances the security of stream ciphers. The hardware implementation can be also correspondingly reduced. An optical solid-integrated scheme is suggested to implement the proposed stream cipher for high-speed encryption and decryption. © 1999 Society of Photo-Optical Instrumentation Engi- neers. (S0091-3286(99)00201-9)

High-security optical integrated stream ciphers

Standard image compression algorithms may not perform well in compressing images for pattern recognition applications, since they aim at retaining image fidelity in terms of perceptual quality rather than preserving spectrally significant information for pattern recognition. New compression algorithms for pattern recognition are therefore investigated, which are based on the modification of the standard compression algorithms to simultaneously achieve higher compression ratio and improved pattern recognition performance. This is done by emphasizing middle and high frequencies and discarding low frequencies according to a new distortion measure for compression. The operations of denoising, edge enhancement, and compression can be integrated in the same encoding process in the proposed compression algorithms. Simulation results show the effectiveness of the proposed compression algorithms.

Mohammad A. Karim

Papers

A new impulse detector for switching median filters

Color image encryption using double random phase encoding

Illumination-invariant pattern recognition with joint-transform-correlator-based morphological correlation

High-security optical integrated stream ciphers

Modification of standard image compression methods for correlation-based pattern recognition