In this paper, we propose the multirate repeating method for alias free subband adaptive filters (AFSAFs) and consider its convergence property. It is shown that we can adjust the convergence speed and the final error of the adaptive filters by varying its two parameters according to the requirements of the applications where the method is applied. The proposed method has two parameters, namely, the number of channel and the number of repetition. We show that by increasing the number of channels we can reduce the final error, and this property is preferred when the signal-to-noise ratio (SNR) is low. On the other hand, we show that the convergence speed of the AFSAF approaches to that of the affine projection algorithm (APA) by increasing the number of repetition. Through the computer simulations, we show the effect of the proposed method.

In this paper, we propose two parallel processing methods for multidimensional (MD) sampling lattice alteration. The use of our proposed methods enables us to alter the sampling lattice of a given MD signal sequence in parallel without any redundancy caused by up- and down-sampling, even if the alteration is rational and non-separable. Our proposed methods are provided by extending two conventional block processing techniques for FIR filtering: the overlap-add method and the overlap-save method. In these proposed methods, firstly a given signal sequence is segmented into some blocks, secondly sampling lattice alteration is implemented for each block data individually, and finally the results are fitted together to obtain the output sequence which is identical to the sequence obtained from the direct sampling lattice alteration. Besides, we provide their efficient implementation: the DFT-domain approach, and give some comments on the computational complexity in order to show the effectiveness of our proposed methods.

One of the problems with subband image coding is the increase in image sizes caused by filtering. To solve this, it has been proposed to process the filtering by transforming input sequence into a periodic one. Then filtering is implemented by circular convolution. Although this technique solves the problem, there are very strong restrictions, i.e., limitation on the filter type and on the filter bank structure. In this paper, development of this technique is presented. Consequently, any type of linear phase FIR filter and any structure of filter bank can be used.

We propose a design method for a two-channel perfect reconstruction FIR filter banks employing linear-phase filters. This type of filter bank is especially important in splitting image signals into frequency bands for subband image cording. Because in such an application, it is necessary to use the combination of linear-phase filters and symmetric image signal, namely linear phase signal to avoid the increase in image size caused by filtering. In this paper, first we summarize the design conditions for two-channel filter banks. Next, we show that the design problem is reduced to a very simple linear equation, by using a half-band filter as a lowpass filter. Also the proposed method is available to lead filters with fewer complexity, which enable us to use simple arithmetic operations. For subband coding, the property is important because it reduces hardware complexity.

This paper reduces the total number of lifting steps of a two dimensional (2D) discrete wavelet transform (DWT) under the constraint that the DWT has full compatibility with a given separable 2D DWT. In a DWT composed of several lifting steps in cascade, a lifting step must wait for a calculation result of its previous lifting step. Therefore more lifting steps bring about longer latency from the input to the output. In this paper, we reduce the total number of lifting steps of a quadruple lifting DWT which is widely utilized as the 9/7 DWT in the JPEG 2000 international standard for image data compression. Firstly, we introduce basic properties for modification of signal flow structure inside a DWT without changing its output. Secondly, we convert the separable 2D quadruple lifting DWT into the non-separable 2D DWT utilizing the basic properties so that the total number of the lifting steps is reduced. As a result, the lifting steps were reduced to 75[%]. Finally, we evaluate the proposed non-separable 2D DWT in respect of compatibility with the conventional separable 2D DWT.

This paper proposes a visual secret sharing (VSS) scheme with efficient pixel expansion which prevents malicious share holders from deceiving an honest share holder. A VSS scheme encrypts a secret image into pieces referred to as shares where each party keeps a share so that stacking a sufficient number of shares recovers the secret image. A cheat prevention VSS scheme gives another piece to each party for verifying whether the share presented by another party is genuine. The proposed scheme improves the contrast of the recovered image and cheat-prevention functionality by introducing randomness in producing pieces for verification. Experimental results show the effectiveness of the proposed scheme.

In many multimedia applications, image encryption has to be conducted prior to image compression. This paper proposes a JPEG-friendly perceptual encryption method, which enables to be conducted prior to JPEG and Motion JPEG compressions. The proposed encryption scheme can provides approximately the same compression performance as that of JPEG compression without any encryption, where both gray scale images and color ones are considered. It is also shown that the proposed scheme consists of four block-based encryption steps, and provide a reasonably high level of security. Most of conventional perceptual encryption schemes have not been designed for international compression standards, but this paper focuses on applying the JPEG and Motion JPEG standards, as one of the most widely used image compression standards. In addition, this paper considers an efficient key management scheme, which enables an encryption with multiple keys to be easy to manage its keys.

A secure identification scheme for JPEG images is proposed in this paper. The aim is to robustly identify JPEG images which are generated from the same original image under various compression levels in security. A property of the positive and negative signs of DCT coefficients is employed to achieve a robust scheme. The proposed scheme is robust against a difference in compression levels, and does not produce false negative matches in any compression level. Conventional schemes that have this property are not secure. To construct a secure identification system, we combine a new error correction technique with 1-bit parity with a fuzzy commitment scheme, which is a well-known biometric cryptosystem. In addition, a way for speeding up the identification is also proposed. The experimental results show the proposed scheme is effective for not only still images, but also video sequences in terms of the querying such as false positive, false negative and true positive matches, while keeping a high level of the security.

We propose a method to retrieve similar and duplicate images from a JPEG (Joint Photographic Image Group) image database. Similarity level is decided based on the DCT (Discrete Cosine Transform) coefficients signs. The method is simple and fast because it uses the DCT coefficients signs as features, which can be obtained directly after partial decoding of JPEG bitstream. The method is robust to JPEG compression, in which similarity level of duplicate images, i.e., images that are compressed from the same original images with different compression ratios, is not disguised due to JPEG compression. Simulation results showed the superiority of the method compared to previous methods in terms of computational complexity and robustness to JPEG compression.

In some applications, such as the echo cancellation problem of satellite-linked communication channels, there occurs a problem of estimation of a long impulse response, which consists of a long flat delay and a short dispersive response region. In this paper, it is shown that the use of the adaptive algorithm based on the frequency domain sampling theorem enables efficient identification of the long impulse response. The use of the proposed technique can lead to the reduction of both the number of adaptive weights and the complexity of flat delay estimation.

This letter proposes an efficient compression scheme for the copyright- and privacy-protected image trading system. The proposed scheme multiplies pseudo random signs to amplitude components of discrete cosine transformed coefficients before the inverse transformation is applied. The proposed scheme efficiently compresses amplitude-only image which is the inversely transformed amplitude components, and the scheme simultaneously improves the compression efficiency of phase-only image which is the inversely transformed phase components, in comparison with the conventional systems.

This letter proposes an efficient lossless compression method for high dynamic range (HDR) images in OpenEXR format. The proposed method transforms an HDR image to an indexed image and packs the histogram of the indexed image. Finally the packed image is losslessly compressed by using any existing lossless compression algorithm such as JPEG 2000. Experimental results show that the proposed method reduces the bit rate of compressed OpenEXR images compared with equipped lossless compression methods of OpenEXR format.

In this paper, we propose a 2-layer lossless coding method for high dynamic range (HDR) images based on range compression and adaptive inverse tone-mapping. Recently, HDR images, which have a wider range of luminance than conventional low dynamic range (LDR) ones, have been frequently used in various fields. Since commonly used devices cannot yet display HDR images, 2-layer coding methods that decode not only HDR images but also their LDR versions have been proposed. We have previously proposed a state-of-the-art 2-layer lossless coding method for HDR images that unfortunately has huge HDR file size. Hence, we introduce two ideas to reduce the HDR file size to less than that of the previous method. The proposed method achieves high compression ratio and experiments show that it outperforms the previous method and other conventional methods.

In this work, a new structure of M-channel linear-phase paraunitary filter banks is proposed, where M is even. Our proposed structure can be regarded as a modification of the conventional generalized linear-phase lapped orthogonal transforms (GenLOT) based on the discrete cosine transform (DCT). The main purpose of this work is to overcome the limitation of the conventional DCT-based GenLOT, and improve the performance of the fast implementation. It is shown that our proposed fast GenLOT is superior to that of the conventional technique in terms of the coding gain. This work also provides a recursive initialization design procedure so as to avoid insignificant local-minimum solutions in the non-linear optimization processes. In order to verify the significance of our proposed method, several design examples are given. Furthermore, it is shown that the fast implementation can be used to construct M-band linear-phase orthonormal wavelets with regularity.

This paper proposes an encryption-then-compression (EtC) system-friendly data hiding scheme for images, where an EtC system compresses images after they are encrypted. The EtC system divides an image into non-overlapping blocks and applies four block-based processes independently and randomly to the image for visual encryption of the image. The proposed scheme hides data to a plain, i.e., unencrypted image and the scheme can take hidden data out from the image encrypted by the EtC system. Furthermore, the scheme serves reversible data hiding, so it can perfectly recover the unmarked image from the marked image whereas the scheme once distorts unmarked image for hiding data to the image. The proposed scheme copes with the three of four processes in the EtC system, namely, block permutation, rotation/flipping of blocks, and inverting brightness in blocks, whereas the conventional schemes for the system do not cope with the last one. In addition, these conventional schemes have to identify the encrypted image so that image-dependent side information can be used to extract embedded data and to restore the unmarked image, but the proposed scheme does not need such identification. Moreover, whereas the data hiding process must know the block size of encryption in conventional schemes, the proposed scheme needs no prior knowledge of the block size for encryption. Experimental results show the effectiveness of the proposed scheme.

In this paper, we propose secure dictionary learning based on a random unitary transform for sparse representation. Currently, edge cloud computing is spreading to many application fields including services that use sparse coding. This situation raises many new privacy concerns. Edge cloud computing poses several serious issues for end users, such as unauthorized use and leak of data, and privacy failures. The proposed scheme provides practical MOD and K-SVD dictionary learning algorithms that allow computation on encrypted signals. We prove, theoretically, that the proposal has exactly the same dictionary learning estimation performance as the non-encrypted variant of MOD and K-SVD algorithms. We apply it to secure image modeling based on an image patch model. Finally, we demonstrate its performance on synthetic data and a secure image modeling application for natural images.

A novel data embedding method for high-quality images, e.g., an image with a peak signal-to-noise ratio of better than 60 [dB] is proposed in this paper. The proposed method precisely generates a watermarked image of the desired and high quality for any images. To do this, this method considers the finite word-length of a luminance value of pixels, i.e., both quantization errors and the range limitation of luminance. The proposed method embeds a watermark sequence, modulated by the mechanism of a spread spectrum scheme, into the dc values of an image in the spatial domain. By employing spread spectrum technology as well as embedding a watermark into the dc values, this method guarantees the high image quality and, simultaneously, provides adequate JPEG tolerance.

In this paper, we propose a secure computation of sparse coding and its application to Encryption-then-Compression (EtC) systems. The proposed scheme introduces secure sparse coding that allows computation of an Orthogonal Matching Pursuit (OMP) algorithm in an encrypted domain. We prove theoretically that the proposed method estimates exactly the same sparse representations that the OMP algorithm for non-encrypted computation does. This means that there is no degradation of the sparse representation performance. Furthermore, the proposed method can control the sparsity without decoding the encrypted signals. Next, we propose an EtC system based on the secure sparse coding. The proposed secure EtC system can protect the private information of the original image contents while performing image compression. It provides the same rate-distortion performance as that of sparse coding without encryption, as demonstrated on both synthetic data and natural images.