In this paper, we propose a reversible data hiding method in the spatial domain for compressed grayscale images. The proposed method embeds secret bits into a compressed thumbnail of the original image by using a novel interpolation method and the Neighbour Mean Interpolation (NMI 1.INTRODUCTIONSecret information exchange is a vital requirement of persons and institutions in society. Channelling secret information over public networks has proven to be very insecure. There is a great need for protective methods for sending secret information.Cryptography is traditionally the first method implemented for protection. Cryptography however, has a few drawbacks. Encrypted data can be easily identified during transmission hence attracting unwanted attention to the packaged information. With increased computing power the possibility of cracking the cryptographic technique increases. Information hiding is an alternative strategy that can be used to protect sensitive secret information. While cryptography protects the content of messages data hiding conceals the existence of secret information.In general, information hiding (also called data hiding or data embedding) includes digital watermarking and steganography [1].Data hiding technology prevents information from being detected, stolen or damaged by unauthorized users during transmission. The word stegano-graphy is a Greek word meaning "covered writing" the art of hiding secret information in ways that prevent detection [2]. The traditional method of encryption [3] can still be applied to the message and then a stegonographic approach used to ensure undetected delivery.Information can be hidden in many ways. Hiding information may involve straight message insertion whereby every bit of information in the cover is encoded or it may selectively embed messages in noisy areas that draw less attention. Messages may also be dispersed in a random fashion throughout the cover data.

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In this paper, we propose a novel reversible steganographic technique to embed secret data into digital images compressed using vector quantization (VQ). The proposed method is based on joint neighboring and predictive coding. The proposed technique can embed n secret bits into one VQ index, where n=1, 2, 3, and 4. Our method uses left and upper neighboring VQ indexes and the difference between the current VQ index and the predicted value produced by the median edge detector predictor to achieve a low bit rate. The experimental results show that the proposed approach obtains embedding rates of 1, 2, 3, and 4 bits per index (bpi) with respective average bit rates of 0.409, 0.471, 0.534, and 0.596 bit per pixel (bpp) for a 256 sized codebook. This confirms that the proposed scheme outperforms three similar reversible data hiding schemes in VQ-compressed domain.

Designing a new reversible data hiding technique with a high embedding rate and a low compression rate for vector quantization (VQ) compressed images is encouraged. This paper proposes a novel lossless data hiding scheme for VQ-compressed images based on the joint neighboring coding technique. The proposed method uses the difference values between a current VQ index and its left and upper neighboring VQ indexes to embed n secret bits into one VQ index, where n = 1, 2, 3, or 4. The experimental results show that the proposed scheme achieves the embedding rates of 1, 2, 3, and 4 bits per index (bpi) with the corresponding average compression rates of 0.420, 0.483, 0.545, and 0.608 bit per pixel (bpp) for a 256 sized codebook. These results confirm that our scheme performs better than other selected reversible data hiding schemes.

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