Shan Suthaharan

Perceptually tuned robust watermarking scheme for digital images

In this paper, we present a digital image watermarking scheme that uses both human visual system and statistical properties. The scheme places watermark in discrete cosine transform (DCT) domain and spreads the watermark effect on the entire image. We have compared our proposed scheme with two other popular schemes and shown that our proposed scheme yields better results in terms of transparency, robustness and maximal capacity requirements.

Perceptually tuned video watermarking scheme using motion entropy masking

We present a watermarking scheme for digital videos that are based on the human visual system characteristics. Our watermarking scheme inserts a perceptually invisible watermark in the discrete cosine transform (DCT) domain. We have shown that the proposed scheme provides better results than two other popular schemes both in transparency and robustness.

Neuro-Fuzzy Modeling and Prediction of VBR MPEG Video Sources

The work presented in this paper intends to apply neuro-fuzzy methods for the modeling and prediction on traffic intensity of digital video sources which are coded with hybrid Motion Compensation/Differential Pulse Code Modulation/Discrete Cosine Transform (MC/DPCM/DCT) algorithm. Although current coding standards recommend constant bit rate (CBR) output by means of a smoothing buffer, the hybrid algorithm inherently produces variable bit rate (VBR) output. This paper describes the novel application of a fuzzy predictor for the purposes of modeling and prediction on video sources. The computation requirement of the fuzzy predictor and its neural network implementation are also discussed. The proposed fuzzy prediction method and its neural network version can be applied to the development of connection admission control, usage parameter control and congestion control algorithms in ATM networks.

Image and edge detail detection algorithm for object-based coding

Abstract This paper presents a novel approach to extract image and edge details that are useful for segmentation of video objects in object-based coding. The proposed approach provides a transform domain technique and uses perceptual properties and edge contrast information in the transform coefficients along with the human visual system weighting to extract image and edge details that are perceptually most significant.

MPEG-compliant joint source/channel coding using discrete cosine transform and substream scheduling for visual communication over packet networks

Quality of Service (QoS)-guarantee in real-time commu- nication for multimedia applications is significantly important. An ar- chitectural framework for multimedia networks based on substreams or flows is effectively exploited for combining source and channel coding for multimedia data. But the existing frame by frame ap- proach which includes Moving Pictures Expert Group (MPEG) can- not be neglected because it is a standard. In this paper, first, we designed an MPEG transcoder which converts an MPEG coded stream into variable rate packet sequences to be used for our joint source/channel coding (JSCC) scheme. Second, we designed a classification scheme to partition the packet stream into multiple substreams which have their own QoS requirements. Finally, we designed a management (reservation and scheduling) scheme for substreams to support better perceptual video quality such as the bound of end-to-end jitter. We have shown that our JSCC scheme is better than two other two popular techniques by simulation and real video experiments on the TCP/IP environment.

Joint Source/Channel Coding to Maximize Perceptual Video Quality on Packet Networks

The QoS-guarantee in real-time communication for multimedia applications is significantly important. An architectural framework for multimedia networks based on substreams or flows are effectively exploited for combining source and channel coding for multimedia data. In this paper, firstly, we designed a source coding scheme based on wavelet transform to exploit the human visual systemss spatial and temporal characteristics of video data. Secondly, we designed a classification scheme to partition video data into multiple substreams which have their own quality of service (QoS) requirements. Finally, we designed a management (reservation and scheduling) scheme for substreams to support better perceptual video quality such as the bound of end-to-end jitter. We have shown that our joint source/channel coding scheme is better than two other schemes by simulation and a real video experiment.

Perceptually most significant edge detection algorithm for object-based coding

The latest digital image coding technique known as the object-based coding is mainly relied on efficient segmentation algorithms. In this paper an edge detail detection technique has been proposed and it can segment the image into objects that are perceptually meaningful. It is a transform domain technique and it makes use of perceptual characteristics, such as frequency distribution decomposition and edge structure decomposition, of transform coefficients thus it detects the perceptually most significant edge details which are useful for segmentation in object-based coding and compression. An experiment has also been conducted to test its robustness to image compression.