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  4. Reversible De-Identification for Lossless Image Compression using Reversible Watermarking
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Category: MTECH DSP/DIP PROJECTS
By MTech Projects
MTech Projects
07.Apr
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Reversible De-Identification for Lossless Image Compression using Reversible Watermarking

PROJECT TITLE :

Reversible De-Identification for Lossless Image Compression using Reversible Watermarking (2014)

ABSTRACT :

De-Identification is a process which can be used to ensure privacy by concealing the identity of individuals captured by video surveillance systems. One important challenge is to make the obfuscation process reversible so that the original image/video can be recovered by persons in possession of the right security credentials. This work presents a novel Reversible De-Identification method that can be used in conjunction with any obfuscation process. The residual information needed to reverse the obfuscation process is compressed, authenticated, encrypted and embedded within the obfuscated image using a two-level Reversible Watermarking scheme. The proposed method ensures an overall single-pass embedding capacity of 1.25 bpp, where 99.8% of the images considered required less than 0.8 bpp while none of them required more than 1.1 bpp. Experimental results further demonstrate that the proposed method managed to recover and authenticate all images considered.

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  • A Weighted OFDM Signal Scheme for Peak-to-Average Power Ratio Reduction of OFDM Signals
  • Image Restoration Using Joint Statistical Modeling in a Space-Transform Domain
  • Reversible De-Identification for Lossless Image Compression using Reversible Watermarking
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  • Design of optimal wavelets for detecting impulse noise in speech
  • Prediction of DCT-based Denoising Efficiency for Images Corrupted by Signal-Dependent Noise
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Previous article: Experimental Analysis of Digital Image Retrieval Using SVD Experimental Analysis of Digital Image Retrieval Using SVD Next article: Power-Constrained Contrast Enhancement Algorithm Using Multi scale Retinex for OLED Display Power-Constrained Contrast Enhancement Algorithm Using Multi scale Retinex for OLED Display
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