Data hiding technologies aim to hide the existence of secret information within digital covers such as images by causing unnoticeable degradation to their quality. Reducing the image distortion and increasing the embedding capacity are the main points that the data hiding techniques revolved around. This article proposes two high payload embedding methods with high stego image quality using the Hue-Saturation-Value (HSV) colour model. The first method is hue-based embedding (HBE) that employs the H plane for hiding one or two bits in non-grey pixels. The second method uses the three HSV components, so it is called three-planes embedding (TPE). In TPE, one bit is hidden in the least significant bit (LSB) of V of the grey pixels, one or two bits in H of the pixels having low saturation or low brightness and one bit in the LSB of S otherwise. The experiments were conducted on 25 images and the results show that HBE hides more data on average than TPE with its quality reaching 60 dB. TPE achieves quality up to 61 dB and capacity reaches 364 Kb. TPE scores the highest capacity among six state-ofthe-art techniques in Red-Green-Blue, HSV, Hue-Saturation-Intensity and YCbCr spaces with the highest average peak signal to noise ratio midst five of them. By embedding 60, 90, and 120 Kb, this TPE attains the best average quality amid all the methods.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Reversible data hiding (RDH) within images is the process of securing data into cover images without degradation. Its challenge is to hide a large payload while taking into account the human visual system so that the distortion of the stego-image is negligible. It is highly desired for the images that have special requirements like the ones in the medical and military fields where the original images are required to be regenerated with no loss after extracting the data. In this paper, we propose an interpolation-based RDH (IRDH) scheme that improves Lee and Huang's scheme and Malik et al.'s scheme by combining their embedding techniques along with the optimal pixel adjustment process (OPAP) in a way that increases the embedding capacity and the visual quality of both the schemes. In this presented scheme, we start by stretching the size of the original image using the existing enhanced neighbor mean interpolation (ENMI) interpolation technique then the data is embedded into the interpolated pixels using our novel embedding method that depends on the intensity of the pixels and the maximized difference values. This innovative scheme presented all steps covering generation of the interpolated image, data embedding, data extraction and image recovery, making it in testing situation to be compared fairly with others. The experimental results demonstrate that the achieved embedding capacity by our hiding technique is more than 537 Kb for all the test images. Also, the experiments show that our proposed scheme has the highest embedding capacity among five current schemes which are Jung and Yoo's scheme, Lee and Huang's scheme, Chang et al.'s scheme, Zhang et al.'s scheme and Malik et al.'s scheme with attractive image security quality.

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