i-manager's Journal on Image Processing (JIP)


Volume 2 Issue 3 July - September 2015

Research Paper

Transform Based Efficient and Robust Watermarking Technique for Medical Images Using Differential Evolution

Venugopal Reddy* , P. Siddaiah**
* Professor, Department of Electronics and Communication Engineering, Nalanda Institute of Engineering and Technology, Guntur, A.P, India.
** Professor and Dean, Department of Electronics and Communication Engineering, University College of Engineering and Technology, Acharya Nagarjuna University, Guntur, A.P, India.
Reddy, V., and Siddaiah, P. (2015). Transform Based Efficient and Robust Watermarking Technique for Medical Images Using Differential Evolution. i-manager’s Journal on Image Processing, 2(3), 1-13. https://doi.org/10.26634/jip.2.3.3600

Abstract

In this research work, a transform based medical image watermarking algorithm is used. Differential Evolution (DE) optimization technique is proposed to ensure that the watermark maintains its structural integrity along with robustness and imperceptibility. Differential Evolution (DE) optimization is employed to optimize the objective function to choose a correct type of wavelet and scaling factor. The water marking is proposed to be implemented using Discrete Wavelet Transforms (DWT), Lifted Wavelet Transform (LWT) and Singular Value Decomposition (SVD) techniques. The encryption is done using RSA and AES encryption algorithms. A Graphical User Interface (GUI) which enables the user to have ease of operation in loading the image, watermark it, encrypt it, and also retrieve the original image whenever necessary is also designed and presented in this paper. The robustness and the integrity of the watermark are tested by measuring different performance parameters and subjecting it to various attacks.

Research Paper

Optical Realization for Tissue Imaging

K. Rajkumar* , V. Padmaja**
* Associate Professor, SR Engineering College, Warangal, Telangana, India.
** Professor, VNR VJIET, Hyderabad, Telangana, India.
Rajkumar, K., and Padmaja, V. (2015). Optical Realization for Tissue Imaging. i-manager’s Journal on Image Processing, 2(3), 14-18. https://doi.org/10.26634/jip.2.3.3601

Abstract

Polarimetric imaging is an emerging technique that uses polarized light to probe the acceptance of the tissue. Basically, tissues are mostly accepted by the clinicians by their chemical processing which takes some time to get the results. Polarization imaging techniques are utilized to understand the variation of polarization properties of optical light which passes through the tissue. The obtained images that are obtained when optical light passes through tissue helps the clinicians to understand and assess the tissue properties and provide knowledge about the functioning of the tissue. In this work, the tissues collected are used for the experimental purpose of tissue interaction with the optical light and is used whether the imaging results of this experiment can be used to study its properties by the signature matrix of the tissue. If the recognizable Mueller Matrix is obtained from this process with rotating optics, then we can understand the polarization variation in the tissue through a novel pixel by pixel analysis technique and via the normalized signature matrix of the tissue.

Research Paper

Comparative Analysis of BM3D and Complex Wavelet Transform based Image Denoising Techniques

S. Swarnalatha* , P. Satyanarayana**, B. Shoban Babu***
* Associate Professor, Department of Electronics and Communication Engineering, Sri Venkateswara University College of Engineering, Tirupati, India.
** Professor, Department of Electronics and Communication Engineering, Annamacharya Institute of Technology and Sciences, Tirupati, India.
Swarnalatha, S., Satyanarayana, P., and Babu, B.S. (2015). Comparative Analysis of BM3D and Complex Wavelet Transform based Image Denoising Techniques. i-manager’s Journal on Image Processing, 2(3), 19-28. https://doi.org/10.26634/jip.2.3.3602

Abstract

This paper presents a comparison between the BM3D and Complex Wavelet Transform based image denoising techniques based on their performance analysis. Complex Wavelet Transforms overcome the limitations of classic Discrete Wavelet Transforms such as, shift sensitivity, poor directionality. Block Matching with 3D filtering (BM3D) technique is a combination of spatial and transform domain filtering techniques. BM3D employs the spatial filtering like Wiener Filtering, and transform based techniques such as Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT); and fusing all the filtered results into a single image to accomplish better performance. As the BM3D techniques use both the spatial and transform based filtering techniques, it achieves a better performance than that of the Complex Wavelet Transforms. However, BM3D based image denoising technique consumes more time than that of Wavelet Transform based image denoising techniques.

Research Paper

Improved Video Watermarking using Discrete Cosine Transform

Dolley Shukla* , Manisha Sharma**
*Associate Professor, Department of Electronics and Telecommunication Engineering, ShriShankaracharya College of Engineering and Technology, Bhilai, India.
** Professor and Head, Department of Electronics and Telecommunication, Bhilai Institute of Technology, Durg, India.
Shukla, D., and Sharma, M. (2015). Improved Video Watermarking using Discrete Cosine Transform. i-manager’s Journal on Image Processing, 2(3), 29-34. https://doi.org/10.26634/jip.2.3.3603

Abstract

In this paper, an improved video watermarking algorithm is presented for copy protection. Each video frame is divided into non-overlapping 8*8 blocks. Each block is a transformed 2D-DCT. After performing the same transformation to all the blocks and frames, embedding of image watermarking is performed with the selected DCT coefficients. Performance of the system is evaluated using peak Signal to Noise Ratio, Mean Square Error, Normalized Mean Square Error, Root Mean Square Error and Absolute Mean Error.

Research Paper

Denoising Technique for Segmentation of Medical Images using Biorthogonal Wavelet Transform

Ritu Agrawal* , Manisha Sharma**
* Research Scholar, Chhattisgarh Swami Vivekananda Technical University, Bhilai, India.
** Professor and Head, Department of Electronics and Telecommunication, Bhilai Institute of Technology, Durg, India.
Agrawal, R., and Sharma, M. (2015). Denoising Technique for Segmentation of Medical Images using Biorthogonal Wavelet Transform. i-manager’s Journal on Image Processing, 2(3), 35-39. https://doi.org/10.26634/jip.2.3.3604

Abstract

The proposed paper is divided into two parts: firstly image denoising and secondly image segmentation. All medical images are corrupted by noise at the time of transmission and acquisition. The goal of denoising is to remove noise while retaining the visual quality of image. Biorthogonal wavelet transform via hard thresholding is used for denoising. The second part of the paper is designed for segmentation of Magnetic Resonance Angiography (MRA) cardio image after denoising. Image segmentation plays a significant role in medical field. The aim of image segmentation is to extract meaningful objects lying in the image. The analysis of MRA images using two segmentation methods namely region growing method and fuzzy c- means method are discussed in the presence of different noise level and comparison of two segmentation techniques based on accuracy has been performed. The experimental results shows that fuzzy cmeans method yields better segmentation result compared to the region growing method.