Kalyan Kumar Halder

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In this paper, a fast image restoration method is proposed to restore the true image from an atmospheric turbulence degraded video. A non-rigid image registration algorithm is employed to register all the frames of the video to a reference frame and determine the shift maps. The First Register Then Average And Subtract-variant (FRTAASv) method is applied to(More)
This paper addresses the problem of stabilizing underwater videos with non-uniform geometric deformations or warping due to a wavy water surface. It presents an improved method to correct these geometric deformations of the frames, providing a high-quality stabilized video output. For this purpose, a non-rigid image registration technique is employed to(More)
In this paper, we present a new approach to track moving objects in videos having a dynamic background. At first, we apply an object detection algorithm that deals with the detection of real objects in a degraded video by separating them from turbulence-induced motions using a two-level thresholding technique. Then, a generalized regression neural network(More)
This paper presents a comparative study between field oriented control (FOC) and direct torque control (DTC), two most popular control strategies for inverter fed interior permanent magnet synchronous motor (IPMSM) drives. The comparison is done in four switch three phase (FSTP) inverter scheme instead of six switch three phase (SSTP) inverter scheme. The(More)
This paper proposes a high accuracy and fast image restoration approach to restore a sequence of atmospheric turbulence degraded frames of a remote object or scene. A coarse-to-fine optical flow technique is employed to estimate the dense motion fields of the frames against a reference frame. The First Register Then Average And Subtract (FRTAAS) method is(More)
A high precision and fast image restoration method is proposed to restore a geometrically corrected image from the atmospheric turbulence degraded video sequence of a static scenery. In this approach, we employ an optical flow technique to register all the frames of the distorted video to a reference frame and determine the flow fields. We use the First(More)
Restoration of a sequence of images influenced by atmospheric turbulence is a challenging task. A new approach for geometrical corrections and noise cancelations of the turbulence degraded frames of a video is presented. The time-averaged frame of the video is used to overcome the geometric deformations through an iterative robust image registration(More)