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A bilateral filter is a local, non-iterative and non-linear technique which aids in removing the noise while preserving edges and details. This work proposes novel highly parallel-pipelined low complex bilateral filter architectures to achieve high throughput, high efficiency, self adaptability and reconfigurability in a real-time noisy environment. The design implements true bilateral filter by adaptively...
Noise in the image are random variations in intensity due to intrinsic or extrinsic sources. This paper proposes a high throughput Fixed Point Discrete Kalman filter (DKF) architecture for denoising images with additive white Gaussian noise (AWGN) at real-time. A linearized state model based on neighbor pixel similarity is used for improving the PSNR of the noisy image. A 5-stage two parallel bi-functional...
Communication system is one of the major areas in which digital signal processing finds direct application. Recent advances in signal processing have helped in enormously reducing the complexity of communication system design and also in improving the performance of the system. Software Defined Radio (SDR) enables in-orbit re-configurability of frequency, modulation scheme, data rate, bandwidth and...
This work presents an FPGA based scalable fixed point QRD architecture based on Givens Rotation algorithm. The proposed QRD core utilizes an efficient pipelined and unfolded 2D MAC based systolic array architecture with dynamic partial reconfiguration (DPR) capability. An improved LUT based Newton-Raphson method is proposed for finding square root and inverse square root which helps in reducing the...
This paper proposes partial reconfigurable FIR filter design using systolic Distributed Arithmetic (DA) architecture optimized for FPGAs. To implement computationally efficient, low power, high speed Finite Impulse Response (FIR) filter a two dimensional fully pipelined structure is used. To reduce the partial reconfiguration time a new architecture for the Look-Up Table (LUT) in distributed arithmetic...
Feature extraction is one of the important tasks in face recognition. Moments are widely used feature extractor due to their superior discriminatory power and geometrical invariance. Moments generally capture the global features of the image. This paper proposes Krawtchouk moment for feature extraction in face recognition system, which has the ability to extract local features from any region of interest...
Feature extraction is one of the important tasks in face recognition. Structural and statistical based approaches are two broad categories of feature extraction. This paper proposes a statistical approach for feature extraction based on Generalized Pseudo-Zernike Moment (GPZM) invariants which is powerful to characterize the image using region based shape features and also invariant to size, tilt,...
Face recognition has found its extensive application in security. An effective method in extracting features increases the efficiency and the recognition rate of the face recognition system and also makes its implementation easier. This paper proposes a two step methodology for improving the recognition rate of the face recognition system. Face images extracted from an acquisition system posses noise,...
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