Detection of Clouds Using SVD and Spectral Properties for NOAA AVHRR Imagery

Volume 4 Issue 2 April - June 2017

Research Paper

Detection of Clouds Using SVD and Spectral Properties for NOAA AVHRR Imagery

B.Ravi Kumar*, B. Anuradha**

* Research Scholar, Department of Electronics and Communication Engineering, S. V. University, Tirupati, India.

** Professor and Head, Department of Electronics and Communication Engineering, S. V. University, Tirupati, India.

Kumar,.B.R. and Anuradha.B (2017). Detection of Clouds Using SVD and Spectral Properties for NOAA AVHRR Imagery. i-manager’s Journal on Image Processing, 4(2), 10-15. https://doi.org/10.26634/jip.4.2.13748

Abstract

Analysis of clouds and their physical properties, such as liquid water content, ice water content, and Reflectivity plays a crucial role in examining the precipitation rate. Till now much work has been done on the NOAA data to examine the clouds and their relation to the rainfall rate. In present work, clouds are detected and classified based on the NOAA-18 AVHRR (Advance Very High Resolution Radiometer) satellite imagery using the SVD (Singular Value Decomposition) property. The eigen values in the SVD help to distinguish between land, snow, and ocean based on the spectral features of the NOAA band 1, 2, and 4 images. The proposed method found the detected clouds with accuracy of 60% using statistical measures. The RGB satellite images are extracted from the NOAA-18 data using ERDAS imagine software which are useful for further processing using MATLAB. All the data used in this work are acquired from NOAA-18 AVHRR satellite imagery installed at S.V. University College of Engineering.

Implementation and analysis of Video Error Concealment using Moment Invariants

Volume 4 Issue 2 April - June 2017

Research Paper

Implementation and analysis of Video Error Concealment using Moment Invariants

Rajani P.K*, Arti Khaparde**, Aditi D Ghuge***

* Assistant Professor, Department of Electronics and Telecommunication Engineering, Pimpri Chinchwad College of Engineering, Pune, India.

** Professor, Department of Electronics and Telecommunication Engineering, Maharashtra Institute of Technology, Pune, India.

*** M.E Student, Department of Electronics and Telecommunication Engineering, Pimpri Chinchwad College of Engineering, Pune, India.

Rajani P.K., Khaparde A. and Ghuge A.D. (2017). Implementation and analysis of Video Error Concealment using Moment Invariants. i-manager’s Journal on Image Processing, 4(2), 1-9. https://doi.org/10.26634/jip.4.2.13747

Abstract

Receiving videos with least error has become one of the main challenges in video applications in recent years. Video error occurrence may be because of loss of data. Video error concealment is technique in which error is removed from the data. In video error concealment, data is recovered back completely. The technique used for that is moment invariance. Video applications are widely used in many domains, such as internet videos, entertainment media, and security applications. In this paper, Video Error Concealment is achieved by Moment Invariance using MATLAB. Some standard videos with different errors in different frames are used to analyze the quality of videos. Error is detected using error function moment invariance technique and corrected by using block matching algorithm. In Moment Invariance method, frames are divided into macroblocks. For analysis, error in macroblocks of different sizes like 16*16 pixel, 8*8 or 4*4 pixel macroblocks are considered in this paper. Error is introduced with different sizes of blocks until error concealment is done. The quality of the video is analyzed using Structural Similarity Index Measurement (SSIM) and Peak Signal to Noise Ratio (PSNR). Result indicates that quality is improved for different error videos.

Implementation of Barrel Distortion CorrectionAlgorithm for Wide Angle Camera Based Systems

Volume 4 Issue 1 January - March 2017

Research Paper

Implementation of Barrel Distortion CorrectionAlgorithm for Wide Angle Camera Based Systems

Smita Laxman Darvatkar*, Sheetal U. Bhandari**

* M.E Student, Department of Electronics and Telecommunication Engineering, Pimpri Chinchwad College of Engineering, Pune, India.

** Professor, Department of Electronics and Telecommunication Engineering, Pimpri Chinchwad College of Engineering, Pune, India.

Darvatkar, S. L., and Bhandari, S.U. (2017). Implementation of Barrel Distortion Correction Algorithm for Wide Angle Camera Based Systems. i-manager’s Journal on Image Processing, 4(1), 43-48. https://doi.org/10.26634/jip.4.1.13523

Abstract

Most of the embedded products designed today are Vision-based systems with camera as a main component for its implementation. The cameras with wide angle lens enable them to capture images giving high-level descriptions of the scene useful for several applications, such as video surveillance, motion analysis, human/object detection, etc. However, images obtained using these wide angle lenses tend to be distorted causing straight lines from the scene to appear as curves in the image plane termed to be as Barrel or Radial Lens Distortion. Such distortion produces less realistic images and affects objects relative sizes, depending on their position in the image. It may be still acceptable in fisheye images, but in fisheye videos, the resulting distortion renders them hard to understand and uncomfortable to watch. It is therefore desirable to correct the barrel distorted images/video before presenting to the end viewer. A lot of research on algorithm that corrects for the distortion of the lens has been done to resolve this problem of radial distortion. Implementing this correction algorithm on a hardware platform can help in developing an ASIC that could be embedded into these Vision-based systems. In this paper, the authors review a framework to correct a wide angle lens distortion based on rectilinear and polynomial based model. The MATLAB implementation of these Distortion correction algorithms is done and comparison of their result is made. It is observed that rectilinear model gives efficient results as compared to polynomial based approach. The hardware platforms used to implement these algorithms are also been discussed. The analysis of these platforms suggest the advanced FPGAs (Field Programmable Gate Arrays) with embedded DSP blocks as a good choice for implementing these Barrel distortion correction algorithms for real time video capturing systems using wide angle lenses making it distortion free.

Enhanced Secure Image Steganography using RSA Algorithm and Hamming Codes

Volume 4 Issue 1 January - March 2017

Research Paper

Enhanced Secure Image Steganography using RSA Algorithm and Hamming Codes

A. Sree Mrudhula*, G. Arun**, C.N. Sujatha***

*-** Department of Electronics and Communication Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, India.

*** Associate Professor, Department of Electronics and Communication Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, India.

Mrudhula, A. S., Arun, G., and Sujatha, C.N. (2017). Enhanced Secure Image Steganography using RSA Algorithm and Hamming Codes. i-manager’s Journal on Image Processing, 4(1), 33-42. https://doi.org/10.26634/jip.4.1.13522

Abstract

Nowadays, the idea of transmitting the text or data safely and securely is the most crucial part. Hiding capacity of the data and its confidentiality plays a vital role in covert communication. A solution for this challenging part of the secure transmission is presented in this paper, wherein the security of transmission is ensured, by first encrypting the data that is to be transmitted by using the RSA algorithm, so the part of security and confidentiality of the message is covered and then Image Steganography is used. It is a technique where the transmitting data is hidden in an image. For hiding the information in an image there are many steganography techniques, in which LSB technique is chosen in this case. In this technique, the data is the text message which is converted into binary format by considering its ASCII values and then the bits of the information is hidden in the least significant bits of the R, G, B values of the pixels of the image.

Detection of Water Level in Lakes using Satellite Images

Volume 4 Issue 1 January - March 2017

Research Paper

Detection of Water Level in Lakes using Satellite Images

S. Priyanka*, M. Narayana**

* PG Student, Department of Electronics and Communication Engineering, Jayaprakash Narayan College of Engineering, Telangana, India.

** Professor & Head, Department of Electronics and Communication Engineering, Jayaprakash Narayan College of Engineering, Telangana, India.

Priyanka, S., and Narayana, M. (2017). Detection of Water Level in Lakes using Satellite Images. i-manager’s Journal on Image Processing, 4(1), 23-32. https://doi.org/10.26634/jip.4.1.13521

Abstract

The objective is to estimate change in water level of lakes using satellite images. High resolution images provided by Landsat satellites are collected and passed through an image processing stage for calculating the lake properties such as Area and Perimeter. The images used in this paper are obtained from the USGS website. All the selected images are cloud free. In this paper, changes in water level are observed by calculating the areas and perimeters of four different lakes in two different times, using satellite images. These satellite images were acquired by Thematic Mapper on the Landsat5 and the Operational Land Imager (OLI) on Landsat 8. To detect the changes, image is classified into two classes, namely land and water. Thus, lake surface and surrounding ground were precisely separated. Then Perimeter (boundary) and Area of the lake are calculated. Area is computed by enumerating black colored pixels and Perimeter by enumerating edges of the lake, i.e. image gradient vector, gives the perimeter of the lake. The Area and Perimeter of the lake change as the water level changes.

An Euclidean Norm Based Nonlinear Filterfor Noise Removal In MR Images

Volume 4 Issue 1 January - March 2017

Research Paper

An Euclidean Norm Based Nonlinear Filterfor Noise Removal In MR Images

G.L.N. Murthy*, B. Anuradha**

* Associate Professor, Department of Electronics and Communication Engineering, LBRCE, Mylavaram, Andhra Pradesh, India.

** Professor, Department of Electronics and Communication Engineering, S.V. Univeristy, Tirupati, Andhra Pradesh, India.

Murthy, G. L. N., and Anuradha, B. (2017). An Euclidean Norm Based Nonlinear Filter for Noise Removal In MR Images. i-manager’s Journal on Image Processing, 4(1), 16-22. https://doi.org/10.26634/jip.4.1.13520

Abstract

Adjacency or neighbourhood plays a vital role while removing noise in many key areas of image processing. This is in view of the fact that once noise corrupts an image, there can be a deviation from original intensity distribution. A location where noise has its impact will clearly have a value which differs from surroundings. The presence of this noise due to various means will definitely affect the accuracy of many computer vision related applications, which is very much critical in medical related applications. In the current work, an algorithm is developed which can handle multiple types of noise with minimum degradation. Unlike conventional filters which directly operate on pixel values, the algorithm concentrates on minimizing the differences between pixels in the process of noise reduction. Peak Signal to Noise Ratio (PSNR) is used as a performance metric for verifying the efficiency of the algorithm.

Analysis of MEMS Based Wireless MicromirrorsSystems for Medical Imaging Applications

Volume 4 Issue 1 January - March 2017

Research Paper

Analysis of MEMS Based Wireless MicromirrorsSystems for Medical Imaging Applications

V. Thrimurthulu*, O.S. Suma Priya**, Sai Pavan Rajesh Sharma***

* Associate Professor & Head, Department of Electronics and Communication Engineering, CREC, Tirupati, Andhra Pradesh, India.

** Assistant Professor, Department of Electronics and Communication Engineering, CREC, Tirupati, Andhra Pradesh, India.

*** PG Student, Department of Electronic Systems, School of Electronic Engineering, Dublin City University, Dublin, Ireland.

Thrimurthulu, V., Priya, O. S. S., and Sharma, S. P. R. (2017). Analysis of Mems Based Wireless Micromirrors Systems for Medical Imaging Applications. i-manager’s Journal on Image Processing, 4(1), 8-15. https://doi.org/10.26634/jip.4.1.13519

Abstract

The advancement in sophisticated technology led to the development of sensors that are helping humans in each and every walk of their life. With the availability of surface mount technology techniques in semiconductor manufacturing systems, many miniaturized devices are currently being produced that are used in sensing parameters like temperature, pressure, level, flow, velocity, thickness, etc. They are designed in such a way that they can even withstand harsh environments and cryogenic conditions with an added advantage of being passive in nature. These devices can be applied to versatile industries, but whereas in medical segment, their significance of impact is more due to wide variety of challenges yet to be answered by conventionally available sensing techniques. As wireless techniques involve signal distortion, transmission problems, and data losses, currently available micro sensors are up to the benchmark, that are able to meet the industry standards by overcoming the general issues in wave propagation.

This paper is a mainly focused medical domain on scanning with MEMS based devices. As imaging of internal body parts in human is most important task involved in medical domain as it helps to identify damaged area, amount of infection, breakage in bones, clots in blood, disease monitoring, clinical diagnostics, etc. Here, a micromirror is used that moves thousands of times per second to generate an invisible grid and that is finally analysed in 3D for imaging. In this model, the dynamic vibrating behaviour of the solid mirror is analysed with air surrounding it using shell elements. The model is solved both for frequency-domain sweep and Eigen frequency study using COMSOL Multiphysics software. The displacement (or velocity) is evaluated at the tip of the mirror for the frequency sweep. This paper focuses on simulation and analysis of micromirror and its corresponding displacement response in terms of torquing force. Current challenges and future scope of micro-electro-mechanical-systems based wireless Micromirror imaging sensor for different medical applications are discussed. This sensor is used for various scanning, fibre optics microscopy applications, and in 3D tissue analysis and for various optical engineering applications.