Ali Gangal

An improved motion-compensated restoration method for damaged color motion picture films

In this paper, we propose an improved motion-compensated restoration method for color motion picture films deteriorated due to flashing blotches. The method consists of an improved multiresolution block matching with log-D search, a rank ordered differences-based blotch detection and 3D vector median filtering for interpolation of missing data, and utilizes five consecutive frames. Performance of the method is tested on artificially corrupted image sequences and real motion picture films, and is compared to that of the three-frame-based method which involves similar algorithms except improved motion estimation and blotch detection. The results show that the method efficiently works even in severely blotched and motion regions in image sequences.

A surface-based method for detection of coronary vessel boundaries in poor quality X-ray angiogram images

In this paper, we propose a surface-based method for simultaneous detection of left and right coronary borders that is suitable for analysis of poor quality X-ray angiogram images. Coronary artery is modelled with a 3D generalized cylinder (GC) with elliptic cross-sections. Based on this model, we developed a 2D surface function for the projection intensity distribution of a vessel part. The parameters associated with vessel edges are estimated from this model. The model takes into account local background intensity, noise and blurring. In simulation and real experiments over a range of imaging conditions, the proposed method consistently produced lower estimation error and variability in detecting edges than our previously reported 1D profile-based method. The improvement is most significant especially for noisy and low-contrast angiograms.

Reconstructing coronary arterial segments from three projection boundaries

Abstract This paper describes a method for the three-dimensional (3D) reconstruction of coronary arterial segments from three projection boundaries. The method is based on the 3D generalized cylinder (GC) model with elliptic cross-sections and mainly consists of a model-based estimation of the vessel boundaries, precise computation of the ellipse parameters of arterial cross-sections from the estimated boundaries, and obtaining the 3D structures by linking consecutive cross-sections. Synthetic and real experiments showed that the method is robust to degradation sources and consequently superior to the two-view method because it uses boundary instead of gray-level information.

Reconstructing ellipsoids from three projection contours

Abstract In this paper, a method for reconstructing ellipsoids from three projection contours is described. Line integral projection of an ellipsoid with uniform density is developed to obtain the equation of the projection contour for any projection view. The reconstruction method starts from the estimation of parameters of a projection contour that has elliptic shape. Then an error function utilizing three sets of ellipse parameters estimated in the previous step is minimized to estimate ellipsoid parameters. Simulation and real experiments demonstrate the validity, usefulness and accuracy of the proposed method.

Design of Gaussian star filter for reduction of periodic noise and quasi-periodic noise in gray level images

This paper proposes a new filtering method for periodic noise reduction in gray level images. The proposed filter consists of two orthogonal Gaussian filters with elliptic profile for each noise peak provided a star shaped filter. Therefore it is called “Gaussian star filter” (GaSF). The filter parameters for each noise peak are estimated by region growing algorithm in image amplitude spectrum. Obtained results show that the periodic noise and quasi periodic noise are effectively reduced by the GaSF filtering method.

A spatiotemporal algorithm for detection and restoration of defects in old color films

A spatiotemporal method is presented for detection and concealment of local defects such as blotches in old color films. Initially, non-local means (NL-means) method which does not require motion estimation is used for noise removal in image sequences. Later, the motion vectors that are incorrectly estimated within defect regions are repaired by taking account of the temporal continuity of motion trajectory. The defects in films are detected by spike detection index (SDI) method, which are easily adapted to color image sequences. Finally, the proposed inpainting algorithm fills in detected defect regions, which is not required to estimate true motion like other approaches. The method is presented on synthetic and real image sequences, and efficient concealment results are obtained.

An effective algorithm for automatic modulation recognition

Based on the previous studies, this article proposes an effective modulation recognition algorithm which is a combination of Higher Order Cumulants (HOC) and Continues Wavelet Transform (CWT). In the Additive White Gaussian Noise (AWGN) the identification of QAM16, QAM32, QAM64, BPSK, QPSK and PSK8 types of modulation were almost successful. In the case of the signal-to-noise ratio (SNR) was higher than -7dB, the identification of QAM16, QAM32 and QAM64 modulation types were 100% successful. While SNR was higher than -2dB, BPSK, QPSK and PSK8 modulation types were identified with success percentage of 100%, 98% and 99%, respectively.

A new sequential decoding algorithm based on branch metric

A new sequential decoding algorithm with an adjustable threshold and a new method of moving through the decoding tree is proposed. Instead of the path metric of the conventional sequential decoding algorithms, the proposed algorithm uses a branch metric based on maximum-likelihood criterion. Two new parameters, the jumping-back distance and going-back distance, are also introduced. The performance of the algorithm for long constraint length convolutional codes is compared to those of the other sequential decoding algorithms and the Viterbi algorithm. The results show that the proposed algorithm is a good candidate for decoding of convolutional codes due to its fast decoding capability and good bit error rate (BER) performance.

A Rate-1 Space-Time Diversity Method for Rotated 4-QAM Constellations

We propose a rate-1 space-time transmit diversity technique. We obtained second-order diversity by transmitting the real and imaginary parts of the symbols from two antennas. With four transmit antennas, we can add Alamouti coding to reach fourth-order transmit diversity. There is no need to detect symbols jointly in either of these applications. It is possible to use both Alamouti coding and Hadamard spreading diversity with the proposed method, thereby obtaining eighth-order (or even higher) transmit diversity. However, joint detection of the symbols is again required at this point. The proposed technique is a suitable space-frequency coding method for OFDM systems. We used computer simulations to compare our technique with the Alamouti coding, quasi-orthogonal space-time block coding (QOSTBC), and orthogonal space–time block coding (OSTBC) methods. We also compared its performance to that of Hadamard spreading diversity. Alamouti coding performs better than the proposed technique at the second order of transmit diversity, but is also limited to that order. The proposed technique performs better than OSTBC at the same order of the transmit diversity. QOSTBC performs slightly better than the proposed technique at the same order of transmit diversity. However, when all methods have the same detection complexity, the proposed technique performs better than both QOSTBC and Hadamard spreading diversity.

Application of Sequential Estimation Algorithm Based on Branch Metric to Frequency-Selective Channel Equalization

In this work, a sequential estimation algorithm based on branch metric is used as channel equalizer to combat intersymbol interference in frequency-selective wireless communication channels. The bit error rate (BER) and computational complexity of the algorithm are compared with those of the maximum likelihood sequence estimation (MLSE), the recursive least squares (RLS) algorithm, the Fano sequential algorithm, the stack sequential algorithm, list-type MAP equalizer, soft-output sequential algorithm (SOSA) and maximum-likelihood soft-decision sequential decoding algorithm (MLSDA). The BER results have shown that whilst the sequential estimation algorithm has a close performance to the MLSE using the Viterbi algorithm, its performance is better than the other algorithms. Beside, the sequential estimation algorithm is the best in terms of computational complexity among the algorithms mentioned above, so it performs the channel equalization faster. Especially in M-ary modulated systems, the equalization speed of the algorithm increases exponentially when compared to those of the other algorithms.