Browsing by Author "Aparna P."

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An Approach for Diagnostically Lossless Coding of Volumetric Medical Data Based on Wavelet and Just-Noticeable-Distortion Model
(2020) Chandrika B.K.; Aparna P.; Sumam David S.
This paper explores a technique for visually/diagnostically lossless coding in the wavelet domain to effectively compress the three-dimensional medical image data. The quantisation module based on Just Noticeable Distortion (JND) for wavelets guarantees the visual quality in the reconstructed data. This method has been further extended to present the Volume of Interest (VOI) based technique that enables to preserve the quality of the diagnostically significant VOI region. The proposed method tested on several datasets outperforms the state-of-the-art methods. Apart from the conventional quality metric, Human Visual System (HVS) based quality metrics are also used to evaluate the visual quality of the reconstructed image. A subjective and objective evaluation carried out for VOI based coder shows that the quality-compression needs of the medical community are well addressed. © 2020 IETE.
Complexity Analysis of Hardware Architectures for Intra Prediction unit of High Efficiency Video Coding (HEVC)
(2020) Shastri S.; Lakshmi; Aparna P.
High efficiency Video Coding (HEVC) is the state-of-the-art video coding technique capable of encoding Ultra High Definition (UHD) videos with better compression efficiency and has better reconstruction quality for the same bitrate as compared to its predecessors. Better compression is possible due to its complex partition and prediction methods. These benefits are at the cost of increased computational complexity, which in turn increases resource consumption and processing time. In this work, we design and implement three different architectures, viz: 1) Fully Sequential Architecture (FSA), 2) Semi-parallel Architecture (SPA) and 3) Fully Parallel Architecture (FPA), for the Intra prediction of HEVC on Field Programmable Gate Arrays (FPGA) and discuss the results. These three configurations are tested for the prediction units of sizes 4×4, 8×8 and 16×16. Results show that FSA uses nearly 70% fewer resources than FPA. Also FSA uses 51.73%, 54.33% and 52.2% less resources than SPA for 4×4, 8×8 and 16×16 block sizes, respectively. Also, the FPA implemented for all three pediction unit (PU) sizes is nearly 22 times and 5 times faster than the FSA and SPA, respectively. © 2020 IEEE.
Distributed video coding based on classification of frequency bands with block texture conditioned key frame encoder for wireless capsule endoscopy
(2020) Sushma B.; Aparna P.
Wireless capsule endoscopy (WCE) has provided remarkable improvement in diagnosing gastrointestinal disorders by scanning the entire digestive tract. The system still need refinement, to upgrade the quality of images, frame rate and battery life. The principal component of the system that can address these issues is low complexity video compressor. Motivated by low computational complexity requirements of WCE video encoding, this paper presents a distributed video coding framework based on frequency bands classification. The lower frequency bands are used to generate good quality side information (SI) as they exhibit high temporal correlation. This reduces the complexity of hash generation at the encoder, thus eliminating the latency in SI creation. Apart from this, SI creation involves only a simple block search and doesn't depend on Wyner–Ziv (WZ) bands. Also different approach for distributed coding of sub-sampled chroma components of WZ frame is proposed. Low complexity JPEG based key frame encoding is proposed that take advantage of WCE image textural properties to reduce the complexity of encoding smooth blocks by 81% at the quantization and encoding stage. Other novel features include use of discrete Tchebichef transform (DTT), Golomb–Rice code for entropy coding. Performance evaluation shows that the proposed method achieves 60% improvement in compression over Motion JPEG with low computational complexity. © 2020 Elsevier Ltd
Efficient architectures for planar and DC modes of intra prediction in HEVC
(2020) Lakshmi; Aparna P.
High efficiency video coding (HEVC) handles the ever increasing global video content with better compression efficiency. Complex partition and increased number of angular modes in intra prediction is one of the factors responsible to achieve this but at the expense of complex computations. In this work, we propose two hardware architectures, Parallel Pipelined Architecture (PPA), and Parallel Datapath Architecture (PDA) for the planar and direct current (DC) modes of intra prediction in HEVC. PPA supports a combination of pipelining and parallel schemes, reuses the multipliers to reduce the hardware resources. PDA includes datapath0 for planar mode and datapath1 for DC mode. They function in parallel. They support all the block sizes and implemented on Artix-7 field programmable gate array (FPGA). The implemented results show that PDA uses 20% fewer resources for block size 4, while PPA uses 20%, 46%, and 62% fewer resources for block sizes 8, 16, and 32, respectively. Detailed synthesis results show that PPA and PDA achieve a throughput of 8 pixels/clock cycle and hence can support 4K videos at 30 frames per second. © 2020 IEEE.
GNSS Intentional Interference Mitigation via Average KF Innovation and Pseudo Track Updation
(2020) Bethi P.; Pathipati S.; Aparna P.
GNSS based navigation is vulnerable to intentional interferences like jamming, meaconing, and spoofing. In the jamming attack, there is no position estimate from the navigation filter. Whereas, in the case of meaconing and spoofing attacks, the navigation track is misguided by projecting the false measurements onto the GNSS receiver. In the above two cases, the measurements are either corrupted by jamming or spoofed. Therefore, to address this problem, this paper presents a novel pseudo-state update and pseudo-covariance update equations for the Kalman filter (KF) at a given epoch to improve the performance of GNSS track. Simulation results reveals that proposed method enhanced the navigation accuracy (by including two adders, two flip flops and a control unit) compared to other traditional methods. Further, it is evident from the results that the proposed approach provided improved performance in track continuity and position root mean square error(PRMSE) compared to existing techniques. © 2020 IEEE.
Impact of Target Tracking Module in GPS Spoofer Design for Stealthy GPS Spoofing
(2020) Bethi P.; Pathipati S.; Aparna P.
This paper presents six different filtering algorithms (Kalman Filter (KF), Reduced State filter (RSF), Separate Covariance filter (SCF), Autonomous Multiple Model (AMM), Generalized Pseudo Bayesian (GPB1 and GPB2), Interactive Multiple Model (IMM)) and its performances to evaluate the impact of target tracking module on GPS spoofing. GPS spoofers are famous for misleading the GPS receivers by imposing mimic GPS signals. The spoofer incorporates the external delays to the captured authentic satellite signals and retransmits towards the GPS receiver to accomplish spoofing. The external delay is a function of the distance between the spoofer and GPS receiver. Therefore, there is a need to estimate the time-varying dynamics of the target by employing a target tracking module to enhance the spoofer performance. In this paper, a comprehensive Simulation study has been carried out to evaluate the performance of various target tracking filters. Simulation results reveals that the multiple model based filters giving good performance for the linear and maneuvering target compared to single model filters. Further, it is evident that the IMM filter gives superior performance in tracking a target and computationally efficient compared to AMM, GPB1, and GPB2 filters. The suggested IMM with KF and EKF configuration provides improved performance (in terms of computational complexity by 43.5%, in tracking position root mean square error (PRMSE) by 26%, and in spoofing PRMSE by 29.6%) compared to two KF filters GPB2 technique. Furthermore, the results also reveals the deployment of IMM based filters into the spoofer module substantially enriches the spoofing efficiency. © 2020 IEEE.
A Mixed Parallel and Pipelined Efficient Architecture for Intra Prediction Scheme in HEVC
(2020) Poola L.; Aparna P.
The complexity of intra prediction in High-Efficiency Video Coding (HEVC) is increased significantly due to the incorporation of inherent features like variable-sized quadtree partitioned coding units and 35 angular modes that help in achieving better compression. This paper presents an efficient hardware architecture for the intra prediction that supports and comprises the above aspects and achieves a higher throughput to support high definition (HD) videos. A compact reusable reference buffer structure is implemented to limit the buffer size to 1 KB. A dedicated arithmetic unit to take advantage of the parallelism present in the prediction algorithm is incorporated, which allows the reuse of multipliers to reduce hardware resources. The loading of reference samples to buffers for prediction causes significant delays which are eliminated in our design. The entire architecture functions as a pipelined unit with no data dependency and generates eight samples/clock cycle in parallel. The design is implemented on a Field Programmable Gate Array (FPGA) platform operating at a frequency of 110 MHz. This makes it possible to support 4 K videos at 30 frames per second, with the resource cost of 16 K logic gates and 122 registers. © 2020 IETE.
Navigation in GPS spoofed environment using m-best positioning algorithm and data association
(2021) Pardhasaradhi B.; Srihari P.; Aparna P.
Intentionally misguiding a global positioning system (GPS) receiver has become a potential threat to almost all civilian GPS receivers in recent years. GPS spoofing is among the types of intentional interference, in which a spoofing device transmits spoofed signals towards the GPS receiver to alter the GPS positioning information. This paper presents a robust positioning algorithm, followed by a track filter, to mitigate the effects of spoofing. It is proposed to accept the authentic GPS signals and spoofed GPS signals into the positioning algorithm and perform the robust positioning with all possible combinations of authentic and spoofed pseudorange measurements. The pseudorange positioning algorithm is accomplished using an iterative least squares (ILS). Further, to efficiently represent the robust algorithm, the M-best position algorithm is proposed, in which a likelihood-based cost function optimizes the positions and only provides M-best positions at a given epoch. However, during robust positioning, the positions evolved due to spoofed pseudorange measurements are removed to overcome GPS spoofing. In order to remove the fake positions being evolved owing to wrong measurement associations in the ILS, a gating technique is applied within the Kalman filter (KF) framework. The navigation filter is a three-dimensional KF with a constant velocity (CV) model, all the position estimates evolved at a specific epoch are observations. Besides, to enhance this technique's performance, the track to position association is performed by using two data association algorithms: nearest neighbor (NN) and probabilistic data association (PDA). Simulations are carried out for GPS receiver positioning by injecting different combinations of spoofed signals into the receiver. The proposed algorithm's efficiency is given by a success rate metric (defined as the navigation track to follow the true trajectory rather than spoofing trajectory) and position root mean square error (PRMSE). © 2013 IEEE.
Stealthy GPS Spoofing: Spoofer Systems, Spoofing Techniques and Strategies
(2020) Bethi P.; Pathipati S.; Aparna P.
Global Positioning System (GPS) and its counterparts are popular for its position, velocity, and time (PVT) information. GPS is vulnerable to spoofing attacks. A comprehensive understanding of GPS spoofing attack requirements, impacts, type of target, and success rates are required to develop anti-spoofing algorithms. This paper aims to provide an understanding regarding the selection of spoofer type, operating location of the spoofer, the impact of spoofing, spoofing techniques, and strategies for performing stealthy GPS spoofing for various applications. This work proposes four novel spoofing techniques (persistent false target, persistent walking target, persistent pull-off target, and persistent walking pull-off target models) and their mathematical realization. Further, it provides efficient spoofing strategies (static pull-off, dynamic pull-off, walking position, and stationary position) for various civilian and military applications. Moreover, various types of targets and their GPS spoofing vulnerabilities have been incorporated (yacht, aircraft, trucks, trains, security tagged criminals, and mobile phones). © 2020 IEEE.
Summarization of Wireless Capsule Endoscopy Video Using Deep Feature Matching and Motion Analysis
(2021) Sushma B.; Aparna P.
Conventional Wireless capsule endoscopy (WCE) video summary generation techniques apprehend an image by extracting hand crafted features, which are not essentially sufficient to encapsulate the semantic similarity of endoscopic images. Use of supervised methods for extraction of deep features from an image need an enormous amount of accurate labelled data for training process. To solve this, we use an unsupervised learning method to extract features using convolutional auto encoder. Furthermore, WCE images are classified into similar and dissimilar pairs using fixed threshold derived through large number of experiments. Finally, keyframe extraction method based on motion analysis is used to derive a structured summary of WCE video. Proposed method achieves an average F-measure of 91.1% with compression ratio of 83.12%. The results indicate that the proposed method is more efficient compared to existing WCE video summarization techniques. © 2013 IEEE.
Texture Classification based Efficient Image Compression Algorithm for Wireless Capsule Endoscopy
(2019) Sushma B.; Aparna P.
This paper presents a novel method for classification of blocks into smooth and edge blocks in transform domain and a compression scheme for Wireless Capsule Endoscopy (WCE) with block classifier. WCE involves capturing, transmission and processing of gastrointestinal images. Power consumption is a critical issue in WCE, as it uses a button battery driven capsule endoscope to capture and transmit images. The captured image needs to be compressed to save the transmission power and low complexity compressor should be used to avoid more power consumption from the compressor itself. JPEG based compression techniques which consists Discrete Cosine Transform(DCT), quantizer and entropy encoder provides the best compression performance with less complexity compared to other various techniques. Pixel distribution in smooth blocks is uniform and energy is compacted only into low frequency bands in spectral domain. Because high frequency bands are almost having zero energy, only low frequency bands are quantized and entropy coded which saves power in processing high bands. Most of the endoscopic image has smooth region, this method is more suitable to WCE. Proposed algorithm improves compression rate by 9% without sacrificing quality compared to JPEG based compression algorithm. © 2019 IEEE.