Rao Tatavarti

An Improved Decision-Based Algorithm for Impulse Noise Removal

The paper proposes an improved fast and efficient decision-based algorithm for the restoration of images that are highly corrupted by Salt-and-Pepper noise. The new algorithm utilizes previously processed neighboring pixel values to get better image quality than the one utilizing only the just previously processed pixel value. The proposed algorithm is faster and also produces better result than a Standard Median Filter (SMF), Adaptive Median Filters (AMF), Cascade and Recursive non-linear filters. The proposed method removes only the noisy pixel either by the median value or by the mean of the previously processed neighboring pixel values. Different images have been tested by using the proposed algorithm (PA) and found to produce better PSNR and SSIM values.

Directional switching median filter using boundary discriminative noise detection by elimination

We propose an accurate and efficient noise detection algorithm for impulse noise removal, called the boundary discriminative noise detection by elimination (BDNDE), which retains the good characteristics of the BDND filter proposed by Ng and Ma (in IEEE Trans. Image Process. 15(6):1506–1516, 2006) while suppressing noise effectively. In order to determine whether a pixel is corrupted, the algorithm first sets the minimum and maximum boundary (threshold) values based on the localized window centered on the pixel. The thresholding helps in achieving low false-alarm and miss-detection rate (even in random noise), even up to 90% noise densities. Extensive simulation results, conducted on gray scale images under a wide range (from 10 to 90%) of noise corruption, clearly demonstrate that our enhanced switching median filter gives better results compared to existing BDND median-based filters, in terms of suppressing impulse noise while preserving image details. The proposed method is algorithmically simple and faster, compared to existing BDND, and more suitable for real-time implementation and application. The new method has shown superior performance in terms of subjective quality in the filtered image as well as objective quality in the peak signal-to-noise ratio (PSNR) measurement to that of the BDND filter.

Automatic Contrast Enhancement for Low Contrast Images: A Comparison of Recent Histogram Based Techniques

In this paper we compare two recent methods for automatic enhancement of the contrast of the image, based on the principle of transforming the skewed histogram of the original image into a uniform histogram. The histogram based gray level grouping (GLG) method and its variants (after Chen et al., 2006) and the fuzzy logic method (after Hanmandlu and Jha, 2006) are evaluated on three different images (gray scale as well as color) in order to ascertain which of the algorithms are better suited across a variety of images from different sensors and having varying characteristics. Based on the visual quality and the Tenengrad criterion we conclude that the FastHSV variant of the GLG method may be applied for automatic contrast enhancement across a wide variety of images.

Fuzzy logic-based automatic contrast enhancement of satellite images of ocean

In this paper, we evaluate the conventional contrast enhancement techniques [histogram equalization (HE), adaptive HE] and the recent gray-level grouping method and the fuzzy logic method in order to find out which of these is well suited for automatic contrast enhancement for satellite images of the ocean, obtained from a variety of sensors. All the techniques evaluated were based on the principle of transforming the skewed histogram of the original image into a uniform histogram. The performance of the different contrast enhancement algorithms are evaluated based on the visual quality and the Tenengrad criterion. The inter comparison of different techniques was carried out on a standard low-contrast image and also three different satellite images with different characteristics. Based on our study, we advocate that a modified fuzzy logic method elucidated in this paper is well suited for contrast enhancement of low-contrast satellite images of the ocean.

Vortex shedding patterns, their competition, and chaos in flow past inline oscillating rectangular cylinders

The flow past inline oscillating rectangular cylinders is studied numerically at a Reynolds number representative of two-dimensional flow. A symmetric mode, known as S-II, consisting of a pair of oppositely signed vortices on each side, observed recently in experiments, is obtained computationally. A new symmetric mode, named here as S-III, is also found. At low oscillation amplitudes, the vortex shedding pattern transitions from antisymmetric to symmetric smoothly via a regime of intermediate phase. At higher amplitudes, this intermediate regime is chaotic. The finding of chaos extends and complements the recent work of Perdikaris et al. [Phys. Fluids 21(10), 101705 (2009)]. Moreover, it shows that the chaos results from a competition between antisymmetric and symmetric shedding modes. For smaller amplitude oscillations, rectangular cylinders rather than square are seen to facilitate these observations. A global, and very reliable, measure is used to establish the existence of chaos.

Detection of tsunami wave generation and propagation using Fiber Bragg Grating sensors

This paper describes the design and development of a Fiber Bragg Grating (FBG) sensor system for monitoring tsunami waves generated in the deep ocean. An experimental setup was designed and fabricated to simulate the generation and propagation of a tsunami wave. The characteristics and efficiency of the developed FBG sensor was evaluated with a standard commercial Digiquartz sensor. For real time monitoring of tsunami waves, FBG sensors bonded to a cantilever is used and the wavelength shifts (ΔλB) in the reflected spectra resulting from the strain/pressure imparted on the FBGs have been recorded using a high-speed Micron Optics FBG interrogation system. The parameters sensed are the signal burst during tsunami generation and pressure variations at different places as the tsunami wave propagates away from the source of generation. The results obtained were compared with the standard commercial sensor used in tsunami detection. The observations suggest that the FBG sensor was highly sensitive and free from many of the constraints associated with the commercial tsunameter.

A novel and pedagogical approach to teach PID controller with LabVIEW signal express

A novel and Pedagogical approach for teaching the PID controller and its tuning parameters to the students and trainee engineers working in Control and Automation Engineering is presented. In short, a trainer/simulator for Proportional- Integral-Derivative Controller is developed. A third order system (Transfer Function) was used. However, there is no limiting factor in using the higher order system in the simulator. Ziegler- Nichols tuning method was used to obtain the optimum or initial values of the PID Controller. LabVIEW Signal Express software developed by NI was used. In specific, the control & design kit module was used. Graphical Interface along with the tuning knobs of the three term controller was highly helpful in finalizing the PID Parameters.

Satellite image processing for oceanic applications using fuzzy logic

In this paper, we have performed a comparative analysis of various conventional contrast enhancement techniques (histogram equalisation and adaptive histogram equalisation), the recent fast grey-level grouping method (Chen et al., 2006a,b), the fuzzy logic method (Hanmandlu and Jha, 2006) and a modified fuzzy logic method (Nair et al., in press) to find out which of these is well suited for automatic contrast enhancement for satellite images of the ocean, obtained from a variety of sensors. The principle of transforming the skewed histogram of the original image into a uniform histogram is used as the basis for all techniques. The performance of the different contrast enhancement algorithms is evaluated based on the visual quality and the Tenengrad criterion. The inter-comparison of different techniques was carried out on a standard low contrast image and also on different satellite images with different characteristics. Based on our study, we conclude that the modified fuzzy logic (Nair et al., in press) is well suited for automatic contrast enhancement of satellite images of the ocean.

Automatic contrast enhancement using Selective Grey-Level Grouping

In this paper, we introduce a method called Automatic Selective Grey-Level Grouping (ASGLG), which enables automatic contrast enhancement of an image based on the principle of transforming the skewed histogram of the original image into a uniform histogram after the recent work on Selective Grey-Level Grouping (SGLG) of the image by Chen et al. (2006a). In SGLG the user needs to specify the greyscale breakpoint and its new location on the greyscale, while the proposed ASLG is automatic and does not require user interface. The histogram based Grey-Level Grouping (GLG) method and its variants (after Chen et al., 2006b) and the Fuzzy Logic method (after Hanmandlu and Jha, 2006) are evaluated on different images in order to ascertain which of the algorithms are better suited across a variety of images from different sensors and having varying characteristics. Based on the visual quality and the Tenengrad criterion we conclude that the ASGLG yields better results.

Optoelectronic Sensor on Moving Platforms for Monitoring Environmental Parameters

The development of an optoelectronic sensor for real time monitoring of environmental parameters in atmosphere and ocean is presented here with envisaged applications onboard automobiles, aircrafts and underwater platforms.