Ch. Naveen

Video encoding techniques based on 3D-DWT

This paper deals with the application of Spatial and Temporal DWT (Discrete Wavelet transform) on the videos. Here we will discuss about three mechanisms and their performance on videos at increased DWT level. In any video processing algorithm, memory is the major criteria. In these three mechanisms dynamic (automatic) DWT level selection and manual level selection is implemented. Here we will also discuss about implementation of different DWT level in spatial and temporal domain. In this paper Haar wavelet is taken as the reference as it has its inherent properties and ease of implementation.

A simple and efficient approach for medical image security using chaos on EZW

In this digital era medical image security is important as they carry highly personal data, which should be kept away from the hackers and unauthorized persons, as these images are transmitted/stored among hospitals and also by health insurance companies. Chaos based cryptography/security has been increased in recent years. In this paper we proposed an algorithm, in which security can be given along with effective compression of image. Our process of providing image security starts with compressing the image using EZW. The output sequence of EZW is converted to 2D and on the 2D data we are going to apply row wise and column wise scrambling algorithm based on chaos. In this paper we are also going to discuss about part of EZW in providing additional security to image along with its main function of compression.

An efficient low dynamic range image compression using improved block based EZW

This papers deals with an efficient image compression technique for images having low dynamic range. The images with low dynamic range generally have low intensity variations. By considering this fundamental characteristic into account we can go for image compression at higher ratio with small modifications to the existing block based EZW algorithm. To achieve the improvement in compression ratio, block-wise Embedded Zero Wavelet (EZW) is applied on the images by forcing all the blocks in the image to take the same number of dominant and sub-ordinate passes. The number of passes applied on each block of the image will be equal to the lowest number of passes taken by one of the blocks in image. This downside the number of passes applied on the image which reduces the number of bits used for encoding the image which successively increase the compression ratio. The proposed algorithm is analyzed with respect to the normal block-wise EZW by mathematical parameters as well as with visual quality. The mathematical parameters chosen for comparison are Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) index. The algorithm is tested from low resolution to UHD resolution images.

Image security using chaos and EZW compression

This paper deals with the image security along with compression. Here we have proposed an algorithm using chaos on EZW compression technique to provide security along with image compression. We had chosen chaos for image security due to its robustness to initial condition and mixing property. Our process of providing image security starts with compressing the image using EZW. The output sequence of EZW is converted to 2-D data and on this 2-D data we apply row and column scrambling algorithm based on chaos. In this paper we also discuss about part of EZW in providing additional security to image along with its main function of compression.

A blind video watermarking technique for indoor video content protection using Discrete Wavelet Transform

In this paper, an highly effective algorithm for copyright protection is proposed using a simple and efficient embedding technique for DWT-based video watermarking for indoor video watermarking applications. Discrete Wavelet Transform (DWT) is applied on the video frame to achieve frequency domain representation of video sequences. The frequency domain representations of DWT are low pass and high pass components of which the low pass component is used to generate the key for each frame. This way the generated key is used at the receiver for extracting the watermark which results in copyright protection. Blind watermarking technique is followed in this paper, this needs only the key for extraction of hidden watermark. The advantage of this method is that it does not require the original video sequences for extraction. To scrutinize the robustness of the proposed algorithm, the original watermark image is equated with those of extracted watermark images by applying several attacks. The results are computed and the performance is evaluated based on the parameters Peak Signal to Noise Ratio (PSNR), Normalized Correlation Coefficient (NC) as well as Structural Similarity index (SSIM). The results illustrates that the process is a blind watermark technique and is highly robust against the different attacks and also for different noisy environments.

Compressed domain video watermarking using EZW and chaos

Video watermarking is must for data security in todays developing world. It is a big challenge as it has too much of data handling and also many compression techniques that may hamper the watermark due to their compression strategies. Thus, in real situations, watermark extraction and providing video security becomes very difficult. Hence, it is essential to have a simple and elegant method of video watermarking. In this paper, we propose a blind watermarking technique in EZW compressed domain. The binary watermark is embedded in video before compression to generate the key. The processed watermarked video is encoded using 3D-DWT and compressed using EZW algorithm. The output obtained from EZW and key generated during watermark embedding is scrambled using chaotic scrambling. At receiver side, the key is used for watermark extraction. As the method uses chaotic scrambling it is also secured and provides a good amount of security over unsecured channels. The proposed method is found to be simple and robust even under compression.

Fast and Memory Efficient 3D-DWT Based Video Encoding Techniques with EZW Based Video Compression Mechanism

This chapter deals with the video encoding techniques using Spatial and Temporal Discrete Wavelet transform (DWT). It discusses about two video encoding mechanisms and their performance at different levels of DWT. Memory is the major criteria for any video processing algorithm, so in this chapter focus on the efficient utilization of the system memory at increased level of spatial and temporal DWT is presented. Out of these two mechanisms, one of the mechanism implements multi resolution analysis in temporal axis. Here the chapter also discuss about implementing the different DWT level in spatial and temporal domain. In this chapter, the Haar wavelet is taken as the reference. Finally, the compression of the videos is achieved by using the standard embedded zero wavelet tree (EZW) mechanism. The performance of the EZW based compression in terms of the PSNR and compression ratio is shown for various videos in this chapter.

Comparative analysis of video compression mechanisms based on EZW coded 3D-DWT and AVI

In this paper, two video compression mechanisms based on 3D-Discrete Wavelet Transform (DWT) and 2D Embedded Zero Wavelet (EZW) are compared depending on the mathematical parameters i.e., Peak Signal-to-Noise Ratio (PSNR) and compression ratio(CR)to that of the standard mechanism. In this paper, we are using Haar wavelet decomposition along with standard EZW for compression, as it has shown improved compression in recent years when used with the techniques like EZW, SPIHT etc. Haar wavelet is chosen because of its ease of implementation and has inherent properties. We apply EZW on frame-by-frame on the encoded video as it is meant for 2D-data only. Here we are adding the extra blocks for video encoding and decoding before and after the existing compression technique i.e., EZW. So, these mechanisms are very easy to implement by just adding the extra blocks of encoding and decoding.