arXiv subjects

Mukul Sarkar

Publications and source records attributed to Mukul Sarkar.

5 recordsLinked to original sources

arXiv2019

Localization: A Missing Link in the Pipeline of Object Matching and Registration

Image registration is a process of aligning two or more images of same objects using geometric transformation. Most of the existing approaches work on the assumption of location invariance. These approaches require object-centric images to perform matching. Further, in absence of intensity level symmetry between the corresponding points in two images, the learning based registration approaches rely on synthetic deformations, which often fail in real scenarios. To address these issues, a combination of convolutional neural networks (CNNs) to perform the desired registration is developed in this work. The complete objective is divided into three sub-objectives: object localization, segmentation and matching transformation. Object localization step establishes an initial correspondence between the images. A modified version of single shot multi-box detector is used for this purpose. The detected region is cropped to make the images object-centric. Subsequently, the objects are segmented and matched using a spatial transformer network employing thin plate spline deformation. Initial experiments on MNIST and Caltech-101 datasets show that the proposed model is able to produce accurate matching. Quantitative evaluation performed using dice coefficient (DC) and mean intersection over union (mIoU) show that proposed method results in the values of 79% and 66%, respectively for MNIST dataset and the values of 94% and 90%, respectively for Caltech-101 dataset. The proposed framework is extended to the registration of CT and US images, which is free from any data specific assumptions and has better generalization capability as compared to the existing rule-based/classical approaches.

cs.CV↗

arXiv2018

1/f Noise Reduction using In-Pixel Chopping in CMOS Image Sensor

In this paper, an in-pixel chopping technique to reduce the low-frequency or 1/f noise of the source follower (SF) transistor in an active pixel sensor (APS) is presented. The SF low-frequency noise is modulated at higher frequencies through chopping, implemented inside the pixel, and in later stage eliminated using low-pass filtering. To implement the chopping, the conventional 3T APS architecture is modified, with only one additional transistor of minimum size per pixel. Reduction in the noise also enhances the dynamic range (DR) of the image sensor. The test circuit is fabricated in UMC 0.18 um standard CMOS technology. The measured results show a reduction of 1/f noise by approximately 22 dB for 50 MHz chopping frequency.

physics.ins-det↗

arXiv2018

Unsupervised Despeckling

Contrast and quality of ultrasound images are adversely affected by the excessive presence of speckle. However, being an inherent imaging property, speckle helps in tissue characterization and tracking. Thus, despeckling of the ultrasound images requires the reduction of speckle extent without any oversmoothing. In this letter, we aim to address the despeckling problem using an unsupervised deep adversarial approach. A despeckling residual neural network (DRNN) is trained with an adversarial loss imposed by a discriminator. The discriminator tries to differentiate between the despeckled images generated by the DRNN and the set of high-quality images. Further to prevent the developed DRNN from oversmoothing, a structural loss term is used along with the adversarial loss. Experimental evaluations show that the proposed DRNN is able to outperform the state-of-the-art despeckling approaches.

cs.CV↗

arXiv2017

Exploiting OxRAM Resistive Switching for Dynamic Range Improvement of CMOS Image Sensors

We present a unique application of OxRAM devices in CMOS Image Sensors (CIS) for dynamic range (DR) improvement. We propose a modified 3T-APS (Active Pixel Sensor) circuit that incorporates OxRAM in 1T-1R configuration. DR improvement is achieved by resistive compression of the pixel output signal through autonomous programming of OxRAM device resistance during exposure. We show that by carefully preconditioning the OxRAM resistance, pixel DR can be enhanced. Detailed impact of OxRAM SET-to-RESET and RESET-to-SET transitions on pixel DR is discussed. For experimental validation with specific OxRAM preprogrammed states, a 4 Kb 10 nm thick HfOx (1T-1R) matrix was fabricated and characterized. Best case, relative pixel DR improvement of ~ 50 dB was obtained for our design.

cs.ET↗

arXiv2017

Analysis and validation of low-frequency noise reduction in MOSFET circuits using variable duty cycle switched biasing

Randomization of the trap state of defects present at the gate Si-SiO$_2$ interface of MOSFET is responsible for the low-frequency noise phenomena such as Random Telegraph Signal (RTS), burst, and 1/\textit{f} noise. In a previous work, theoretical modelling and analysis of the RTS noise in MOS transistor was presented and it was shown that this 1/\textit{f} noise can be reduced by decreasing the duty cycle ($f_{D}$) of switched biasing signal. In this paper, an extended analysis of this 1/\textit{f} noise reduction model is presented and it is shown that the RTS noise reduction is accompanied with shift in the corner frequency ($f_{c}$) of the 1/\textit{f} noise and the value of shift is a function of continuous ON time ({$T_{on}$}) of the device. This 1/\textit{f} noise reduction is also experimentally demonstrated in this paper using a circuit configuration with multiple identical transistor stages which produces a continuous output instead of a discrete signal. The circuit is implemented in 180~nm standard CMOS technology, from UMC. According to the measurement results, the proposed technique reduces the 1/\textit{f} noise by approximately 5.9 dB at $f_{s}$ of 1~KHz for 2 stage, which is extended up to 16 dB at $f_{s}$ of 5 MHz for 6 stage configuration.

cond-mat.other↗