Kirat Pal

Shadow Detection and Removal from Remote Sensing Images using NDI and Morphological Operators

Shadows appear in remote sensing images due to elevated objects. Shadows cause hindrance to correct feature extraction of image features like buildings ,towers etc. in urban areas it may also cause false color tone and shape distortion of objects, which degrades the quality of images. Hence, it is important to segment shadow regions and restore their information for image interpretation. This paper presents an efficient and simple approach for shadow detection and removal based on HSV color model in complex urban color remote sensing images for solving problems caused by shadows. In the proposed method shadows are detected using normalized difference index and subsequent thresholding based on Otsu’s method. Once the shadows are detected they are classified and a non shadow area around each shadow termed as buffer area is estimated using morphological operators. The mean and variance of these buffer areas are used to compensate the shadow regions.

All-pass filters using DDCC- and MOSFET-based electronic resistor

The main motivation in this paper is to draw attention to the tunability and input-signal amplitude limitations when a nonlinear device is used as a resistor. For this purpose, two first-order all-pass filters are proposed using differential difference current conveyor (DDCC), a capacitor and a resistor without element-matching restriction. These all-pass filter circuits can be made electronically tunable with electronic resistors. Tunability and input-signal amplitude limitations of the proposed circuits due to the operational restrictions of the electronic resistors are examined. PSPICE simulations confirm the validity and the practical utility of the proposed circuits. Copyright

CMOS-controlled inverting CDBA with a new all-pass filter application

In this study, new active elements called inverting current differencing buffered amplifier (ICDBA) and current-controlled ICDBA (C-ICDBA) are presented. Unlike current differencing buffered amplifier (CDBA), their voltage transfer ratio between the Z and W terminals are equal to minus one. Furthermore, CMOS implementations of the C-ICDBA and current-controlled CDBA (C-CDBA) are shown. Moreover, a novel first-order all-pass filter is proposed to show advantages and new circuit producing capability of the ICDBA/C-ICDBA. Lastly, an electronically tunable band-pass filter is given as an application example using the presented all-pass filter. The measured and simulation results are in good agreement with the theoretical ones. Copyright

All-pass filter for rich cascadability options easy IC implementation and tunability

This paper presents two current-mode all-pass sections, employing only grounded components, which is important from the integrated circuit (IC) implementation point of view. The use of the grounded capacitor allows the IC implementation with standard CMOS technologies. The circuits can be made electronically tunable due to grounded resistors that can be realized by using voltage controlled MOS based resistors. In addition, the circuits have both low input impedance and high output impedance for easy cascadability. The stability analysis proves that the circuits are stable. SPICE simulations and experimental results are in close agreement with the theory.

A Fuzzy Kohonen Local Information C-Means Clustering for Remote Sensing Imagery

ABSTRACT This paper presents a neuro fuzzy clustering algorithm, Fuzzy Kohonen Local Information C-Means (FKLICM), for classification of remote sensing images. The proposed algorithm is a hybridization of the conventional Kohonen clustering network and Fuzzy Local Information C-Means (FLICM) to produce a much more efficient and accurate clustering algorithm. The proposed algorithm first forms a fused image with three Multispectral bands and pan band of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) using the Brovey transform. The fused image is a three band image with higher resolution and better visual perception. The fused image is reduced to a one-dimensional image using principal component analysis (PCA). The FKLICM algorithm is applied on the PC-1 image to classify the remote sensing image into different land cover types. Integrating the neural network with a fuzzy system combines the advantages and overcomes the limitations of both technologies. The experimental results of the proposed algorithm are compared with two other algorithms, FCM and GIFP-FCM. The classification results and accuracy assessment show that FKLICM yields better results than the other methods.

DDCC based all-pass filters using minimum number of passive elements

In this study, three first order all-pass filters are proposed using differential difference current conveyor (DDCC), a capacitor and a resistor without element-matching restriction. The theoretical results are verified with SPICE simulations.

A HIGH INPUT IMPEDANCE VOLTAGE-MODE ALL-PASS/NOTCH FILTER USING A SINGLE VARIABLE GAIN CURRENT CONVEYOR

In this paper, a novel circuit for realizing voltage-mode first-order and second-order all-pass filter responses as well as second-order notch filter response depending on the passive component choice, is presented. This circuit has high input impedance; thus, it is easy to cascade the introduced filter with other voltage-mode topologies. Also, it uses a single Variable Gain Current Conveyer — VGCCII and only grounded capacitors. SPICE simulation results based on 0.35 μm TSMC CMOS technology parameters are given to confirm the theory.

Prediction of ground motion parameters using randomized ANFIS (RANFIS)

Prediction of ground motion parameters using hybrid soft computing technique.The neuro-fuzzy inference system uses Sugeno type fuzzy rules with a randomized fuzzy layer and a linear neural network output layer.Faster prediction of peak ground acceleration, velocity and displacement with increased accuracy. In this paper, a novel neuro-fuzzy learning machine called randomized adaptive neuro-fuzzy inference system (RANFIS) is proposed for predicting the parameters of ground motion associated with seismic signals. This advanced learning machine integrates the explicit knowledge of the fuzzy systems with the learning capabilities of neural networks, as in the case of conventional adaptive neuro-fuzzy inference system (ANFIS). In RANFIS, to accelerate the learning speed without compromising the generalization capability, the fuzzy layer parameters are not tuned. The three time domain ground motion parameters which are predicted by the model are peak ground acceleration (PGA), peak ground velocity (PGV) and peak ground displacement (PGD). The model is developed using the database released by PEER (Pacific Earthquake Engineering Research Center). Each ground motion parameter is related to mainly to four seismic parameters, namely earthquake magnitude, faulting mechanism, source to site distance and average soil shear wave velocity. The experimental results validate the improved performance of the machine, with lesser computation time compared to prior studies.

A novel edge preserving filter for impulse noise removal

This paper proposes an edge preserving filter for removal of impulse noise. Digital images received from various sources are often degraded due to impulse noise and thus become unsuitable for further processing. To overcome this degradation removal of impulse noise is very important. In this paper an effective and efficient method of impulse noise removal is proposed which not only removes noise but also preserves edges. The algorithm first finds noisy, noise free and edge pixels. Then it replaces the noisy pixel with a pixel from its neighbourhood which is nearest to the adaptive median of the noisy pixel, this removes the noise as well as preserves edges and fine image details.

NEW ALL-PASS FILTER CIRCUIT COMPENSATING FOR C-CDBA NON-IDEALITIES

In this paper, a CMOS current controlled current differencing buffered amplifier (C-CDBA) realization is presented. Also, a new first-order all-pass filter that compensates for some C-CDBA non-idealities is given as an application example. The all-pass filter circuit has low output impedance for easy cascadability and it can be made electronically tunable using the proposed C-CDBA implementation. The theoretical results are verified with SPICE simulations.