Digital source identification is one of the most important problems in the field of multimedia forensics. While Standard Dynamic Range (SDR) images are commonly analyzed, High Dynamic Range (HDR) images are a less common research subject, which leaves space for further analysis. In this paper, we present a novel database of HDR and SDR images captured in different conditions, including various capturing motions, scenes and devices. As a possible application of this dataset, the performance of the well-known reference pattern noise-based source identification algorithm was tested on both kinds of images. Results have shown difficulties in source identification conducted on HDR images, due to their complexity and wider dynamic range. It is concluded that capturing conditions and devices themselves can have an impact on source identification, thus leaving space for more research in this field.

A New Dataset for Source Identification of High Dynamic Range Images

For sensitive areas that even the slight distortion in images is not tolerated, we propose a prediction error expansion-based reversible data hiding algorithm which can embed reversible watermark in high dynamic range (HDR) image with low distortion. On the one hand, considering unique floating-point storage format and perceptual characteristics of HDR image, the multiple carriers are generated with low distortion and various characteristics to improve the embedding capacity. On the other hand, multi-model predictor and multi-level embedding strength are adopted adaptively to realize multi-level reversible HDR image information hiding based on prediction error expansion. The experimental results show that the proposed algorithm has good invisibility by making full use of HDR image characteristics. Meanwhile, the multiple strategies of multiple carriers, multi-model predictor and multi-level embedding strength, which further improve the embedding capacity and security of the algorithm, can meet the needs of sensitive areas such as medical processing, judicial authentication, and so on.

Reversible data hiding scheme for high dynamic range images based on multiple prediction error expansion

Data compression is the process of encoding information using fewer bits (or other information bearing units) than an uuencoded representation would use, through use of specific encoding schemes. Using this we can achieve reduced resource consumption and security of data as well. Data Compression may be categorized in following two categories. (A)Lossless Compression algorithms usually exploit statistical redundancy in such a way as to represent the sender’s data more concisely without error. (B)Lossy Compression is possible if some loss of some fidelity is acceptable .Lossy schemes accept some losss of data in order to achieve higher compression .Lossy data compression is better known as rate-distortion theory. Shannon formulated the theory of data compression .Lossless data compression theory and rate-distortion theories are known collectively as Source Coding theory.

Lossless Data Compression Techniques with Block Coding: An explanation

Watermarking describes methods to hide information, such as a number or text or image in digital media format like image, video or audio. Watermarking techniques can be classified as Visible, Invisible, Robust and Fragile.This paper focuses on reversible watermarking, which is one of the methods toimplement fragile watermarking. Reversible watermarking is a data hiding technique andit restores the original image without any distortion. Now a day’s, various techniques are well known to perform reversible watermarking such as Histogram Shifting (HS), Difference Expansion (DE), Prediction Error Expansion(PEE), Integer Transform, Least Significant Bit (LSB), Wavelet and Interpolation Technique etc. This paper conductsa comprehensive assessment and performance overview of all existing techniques. PSNR, MSE, BER, RMSE, MAE and NPCR these are the performance measures used to evaluate all different techniques.

Comprehensive assessment, performance overview and review of all existing techniques of reversible image watermarking for medical imaging

In this paper, a generic visible watermarking with a capability of lossless image recovery is proposed. This method based on the use of deterministic one-to-one compound mapping of pixel values a variety of visible watermarks on the cover image. The image conversion for watermarks normal image into HDR image are used in various image segmentation applications. During image conversion from watermarked into HDR image. The embedded watermark will be erased due to the usage of tone mapping in HDR image conversion. In this paper we have proposed a new technique for embedding a watermark which will not be erased during image conversion from normal image to HDR image. Our proposed system that, the original HDR image is transformed to a reference image by applying logLUV transformation. Finally the reverse log transform is applied to obtain the watermarked version of the given original image when a generic TM (Tone mapping) is applied to the watermarked HDR image, the watermark is still presents long as the assumption of similarly between the log transform and TM. The compound mappings are proved to be reversible, which allows for lossless recovery of original image from watermark image.

http://paper.ijcsns.org/07_book/201305/20130519.pdf

A. Nagurammal

Papers

Lossless Image Watermarking for HDR Images Using Tone Mapping