Reversible Image Data Hiding with Contrast Enhancement

   December 11, 2017    Comments Off on Reversible Image Data Hiding with Contrast Enhancement    Posted in: IEEE 2017, MATLAB

Reversible Image Data Hiding with Contrast Enhancement

ABSTRACT:

In this letter, a novel reversible data hiding (RDH) algorithm is proposed for digital images. Instead of trying to keep the PSNR value high, the proposed algorithm enhances the contrast of a host image to improve its visual quality. The highest two bins in the histogram are selected for data embedding so that histogram equalization can be performed by repeating the process. The side information is embedded along with the message bits into the host image so that the original image is completely recoverable. The proposed algorithm was implemented on two sets of images to demonstrate its efficiency. To our best knowledge, it is the first algorithm that achieves image contrast enhancement by RDH. Furthermore, the evaluation results show that the visual quality can be preserved after a considerable amount of message bits have been embedded into the contrast-enhanced images, even better than three specific MATLAB functions used for image contrast enhancement.

EXISTING SYSTEM:

  • Reversible Data Hiding (RDH) has been intensively studied in the community of signal processing. Also referred as invertible or lossless data hiding, RDH is to embed a piece of information into a host signal to generate the marked one, from which the original signal can be exactly recovered after extracting the embedded data.
  • The technique of RDH is useful in some sensitive applications where no permanent change is allowed on the host signal.
  • In the literature, most of the proposed algorithms are for digital images to embed invisible data or visible watermark. To evaluate the performance of a RDH algorithm, the hiding rate and the marked image quality are important metrics.

 

DISADVANTAGES OF EXISTING SYSTEM:

  • There exists a trade-off between them because increasing the hiding rate often causes more distortion in image content.
  • To our best knowledge, there is no existing RDH algorithm that performs the task of contrast enhancement so as to improve the visual quality of host images.
  • To measure the distortion, the peak signal-to-noise ratio (PSNR) value of the marked image is often calculated. Generally speaking, direct modification of image histogram provides less embedding capacity.

 

PROPOSED SYSTEM:

  • In this project, we aim at inventing a new RDH algorithm to achieve the property of contrast enhancement instead of just keeping the PSNR value high. In principle, image contrast enhancement can be achieved by histogram equalization.
  • To perform data embedding and contrast enhancement at the same time, the proposed algorithm is performed by modifying the histogram of pixel values. Firstly, the two peaks (i.e. the highest two bins) in the histogram are found out. The bins between the peaks are unchanged while the outer bins are shifted outward so that each of the two peaks can be split into two adjacent bins.
  • To increase the embedding capacity, the highest two bins in the modified histogram can be further chosen to be split, and so on until satisfactory contrast enhancement effect is achieved. To avoid the overflows and under-flows due to histogram modification, the bounding pixel values are pre-processed and a location map is generated to memorize their locations. For the recovery of the original image, the location map is embedded into the host image, together with the message bits and other side information. So blind data extraction and complete recovery of the original image are both enabled.

ADVANTAGES OF PROPOSED SYSTEM:

  • Distortion is less.
  • To increase the embedding capacity.
  • Increase visual quality.
  • The proposed algorithm was applied to two set of images to demonstrate its efficiency. To our best knowledge, it is the first algorithm that achieves image contrast enhancement by RDH.
  • Furthermore, the evaluation results show that the visual quality can be preserved after a considerable amount of message bits have been embedded into the contrast-enhanced images, even better than three specific MATLAB functions used for image contrast enhancement.

 

 

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

 

  • System : Pentium IV 2.4 GHz.
  • Hard Disk : 40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.

 

 

SOFTWARE REQUIREMENTS:

 

  • Operating system : Windows XP/7.
  • Coding Language : MATLAB
  • Tool : MATLAB R2013A

 

REFERENCE:

Hao-Tian Wu, Member, IEEE, Jean-Luc Dugelay, Fellow, IEEE, and Yun-Qing Shi, Fellow, IEEE , “Reversible Image Data Hiding with Contrast Enhancement”, IEEE SIGNAL PROCESSING LETTERS, VOL. 22, NO. 1, JANUARY 2015.

  

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