Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Existing image-based reversible data hiding (RDH) methods tend to focus on increasing embedding capacity, but few consider keeping or improving visual image quality. Wu et al. proposed a new RDH method with contrast enhancement (RDH-CE) by pair-wisely expanding the histogram to the lor end and upper end. RDH-CE is especially valuable in exploiting the details of poorly illustrated images for which the visibility of image details is more important than just keeping PSNR high. Hover, obvious visual image distortion appears when embedding level gets high, and embedding capacity is relatively low when embedding level is small. , Wu et al.'s work is improved from three perspectives, namely image contrast enhancement, visual distortion reduction, and embedding capacity increment. The image contrast is improved by making the histogram shifting process adaptive to the histogram distribution characteristics, the image visual distortion is reduced by cutting off half the modification range of pixels induced in histogram pre-shifting, and the embedding capacity is increased by exploiting the pixel value ordering technique at the early stage of data embedment. Experimental result proves that the proposed work is effective in improving image contrast, reducing visual image distortion, and increasing embedding capacity. >Adaptive histogram shifting improves the image contrast for RDH methods.Bidirectional histogram pre-shifting alleviates visual image distortion.The pixel value ordering technique increases the embedding capacity.An alternative way can better evaluate the marked image quality.
['Haishan Chen', 'Jiangqun Ni', 'Wien Hong', 'Tung-Shou Chen']
I am writing a research paper on a idea Reversible data hiding with contrast enhancement using adaptive histogram shifting and pixel value ordering
[{"from": "human", "value": "I am writing a research paper on a idea Reversible data hiding with contrast enhancement using adaptive histogram shifting and pixel value ordering"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Existing image-based reversible data hiding (RDH) methods tend to focus on increasing embedding capacity, but few consider keeping or improving visual image quality. Wu et al. proposed a new RDH method with contrast enhancement (RDH-CE) by pair-wisely expanding the histogram to the lor end and upper end. RDH-CE is especially valuable in exploiting the details of poorly illustrated images for which the visibility of image details is more important than just keeping PSNR high. Hover, obvious visual image distortion appears when embedding level gets high, and embedding capacity is relatively low when embedding level is small. , Wu et al.'s work is improved from three perspectives, namely image contrast enhancement, visual distortion reduction, and embedding capacity increment. The image contrast is improved by making the histogram shifting process adaptive to the histogram distribution characteristics, the image visual distortion is reduced by cutting off half the modification range of pixels induced in histogram pre-shifting, and the embedding capacity is increased by exploiting the pixel value ordering technique at the early stage of data embedment. Experimental result proves that the proposed work is effective in improving image contrast, reducing visual image distortion, and increasing embedding capacity. >Adaptive histogram shifting improves the image contrast for RDH methods.Bidirectional histogram pre-shifting alleviates visual image distortion.The pixel value ordering technique increases the embedding capacity.An alternative way can better evaluate the marked image quality."}]