S. Bouguezel

A new radix-2/8 FFT algorithm for length-q/spl times/2/sup m/ DFTs

In this paper, a new radix-2/8 fast Fourier transform (FFT) algorithm is proposed for computing the discrete Fourier transform of an arbitrary length N=q/spl times/2/sup m/, where q is an odd integer. It reduces substantially the operations such as data transfer, address generation, and twiddle factor evaluation or access to the lookup table, which contribute significantly to the execution time of FFT algorithms. It is shown that the arithmetic complexity (multiplications+additions) of the proposed algorithm is, in most cases, the same as that of the existing split-radix FFT algorithm. The basic idea behind the proposed algorithm is the use of a mixture of radix-2 and radix-8 index maps. The algorithm is expressed in a simple matrix form, thereby facilitating an easy implementation of the algorithm, and allowing for an extension to the multidimensional case. For the structural complexity, the important properties of the Cooley-Tukey approach such as the use of the butterfly scheme and in-place computation are preserved by the proposed algorithm.

A low-complexity parametric transform for image compression

In this paper, a one-parameter eight-point orthogonal transform suitable for image compression is proposed. An algorithm for its fast computation is developed and an efficient structure for a simple implementation valid for all possible values of its independent parameter is proposed. It is shown that an appropriate selection of the values of the parameter results in a number of new multiplication-free transforms having a good compromise between the computational complexity and performance. Applying the proposed transform to image compression, we show that it outperforms the existing transforms having complexities similar to that of the proposed one.

A novel transform for image compression

In this paper, we propose an orthogonal multiplication-free transform of order that is an integral power of two by an appropriate extension of the well-known fourthorder integer discrete cosine transform. Moreover, we develop an efficient algorithm for its fast computation. It is shown that the computational and structural complexities of the algorithm are similar to that of the Hadamard transform. By applying the proposed transform to image compression, we show that it outperforms the existing transforms having complexities similar to that of the proposed one.

Binary Discrete Cosine and Hartley Transforms

In this paper, a systematic method for developing a binary version of a given transform by using the Walsh-Hadamard transform (WHT) is proposed. The resulting transform approximates the underlying transform very well, while maintaining all the advantages and properties of WHT. The method is successfully applied for developing a binary discrete cosine transform (BDCT) and a binary discrete Hartley transform (BDHT). It is shown that the resulting BDCT corresponds to the well-known sequency-ordered WHT, whereas the BDHT can be considered as a new Hartley-ordered WHT. Specifically, the properties of the proposed Hartley-ordering are discussed and a shift-copy scheme is proposed for a simple and direct generation of the Hartley-ordering functions. For software and hardware implementation purposes, a unified structure for the computation of the WHT, BDCT, and BDHT is proposed by establishing an elegant relationship between the three transform matrices. In addition, a spiral-ordering is proposed to graphically obtain the BDHT from the BDCT and vice versa. The application of these binary transforms in image compression, encryption and spectral analysis clearly shows the ability of the BDCT (BDHT) in approximating the DCT (DHT) very well.

A fast 8×8 transform for image compression

In this paper, we propose an efficient 8×8 transform matrix for image compression by appropriately introducing some zeros in the 8×8 signed DCT matrix. We show that the proposed transform is orthogonal, which is a highly desirable property. In order to make this novel transform more attractive for recent real-time applications, we develop an efficient algorithm for its fast computation. By using this algorithm, the proposed transform requires only 18 additions to transform an 8-point sequence. Compared to the existing 8×8 approximated DCT matrices, it is shown that savings of 25% in the number of arithmetic operations can easily be achieved using the proposed transform operator without noticeable degradations in the reconstructed images. We also present simulation results using some standard test images to show the efficiency of the proposed transform in image compression.

Improved radix-4 and radix-8 FFT algorithms

In this paper, improved algorithms for radix-4 and radix-8 FFT are presented. This is achieved by re-indexing a subset of the output samples resulting from the conventional decompositions in the radix-4 and radix-8 FFT algorithms. These modified radix-4 and radix-8 algorithms provide savings of more than 33% and 42% respectively in the number of twiddle factor evaluations or accesses to the lookup table compared to the corresponding conventional FFT algorithms without imposing any additional complexity.

New Parametric Discrete Fourier and Hartley Transforms, and Algorithms for Fast Computation

In this paper, we propose a new reciprocal-orthogonal parametric discrete Fourier transform (DFT) by appropriately replacing some specific twiddle factors in the kernel of the classical DFT by independent parameters that can be chosen arbitrarily from the complex plane. A new class of parametric unitary transforms can be obtained from the proposed transform by choosing all its independent parameters from the unit circle. One of the special cases of this class is then exploited for developing a new one-parameter involutory discrete Hartley transform (DHT). The proposed parametric DFT and DHT can be computed using the existing fast algorithms of the DFT and DHT, respectively, with computational complexities similar to those of the latter. Indeed, for some special cases, the proposed transforms require less number of operations. In view of the fact that the transforms of small sizes are used in some image and video compression techniques and employed as building blocks for larger size transform algorithms, we develop new algorithms for the proposed small-size transforms. The proposed parametric DFT and DHT, in view of the introduction of the independent parameters, offer more flexibility in achieving better performance compared to the classical DFT and DHT. As examples of possible applications of the proposed transforms, image compression, Wiener filtering, and spectral analysis are considered.

A New Class of Reciprocal–Orthogonal Parametric Transforms

In this paper, a new class of reciprocal-orthogonal parametric (ROP) transforms having 3N/2 independent parameters for a sequence length N that is a power of two is proposed. The basic idea behind the proposed transforms is to appropriately combine a new parametric kernel with that of the well-known Walsh-Hadamard transform that results in a square parametric matrix operator of order N with some very interesting properties. It is shown that the inverse matrix operator of the proposed class of transforms can be easily obtained by taking the reciprocal of each of the entries of the forward matrix and then transposing the resulting matrix. In addition, a simple method is introduced in order to facilitate the generation of the matrix operator of the proposed ROP transforms. This method is then used specifically to construct new classes of unitary and multiplication-free transforms. Many other new transforms, as well some of the existing ones, can be derived from these proposed ROP transforms. An efficient algorithm is developed for a fast computation of the proposed transforms. In view of the availability of this fast algorithm and the property of easily computable inverse transform, the proposed ROP transforms can be used in many transform-based applications, with their independent parameters providing more degrees of freedom such as affording an additional secret key in watermarking and encryption applications.

A Split Vector-Radix Algorithm for the 3-D Discrete Hartley Transform

In this paper, we propose a three-dimensional (3-D) split vector-radix fast Hartley transform (FHT) algorithm. The main idea behind the proposed algorithm is that the radix-2/4 approach is introduced in the decomposition of the 3-D discrete Hartley transform by using an appropriate index mapping and the Kronecker product. This provides an algorithm based on a mixture of radix-(2times2times2) and radix-(4times4times4) index maps and has a butterfly that is characterized by simple closed-form expressions. This algorithm offers substantial reductions in the numbers of multiplications, additions, data transfers, and twiddle factor evaluations or accesses to the look-up table, without a significant increase in the structural complexity compared to that of the existing 3-D vector radix FHT algorithm

Image encryption using the reciprocal-orthogonal parametric transform

Discrete transforms have been widely used in various signal processing applications. Specifically, transform-based data encryption techniques have become attractive for many recent communication systems. In this paper, we propose a fast and efficient image encryption method based on the reciprocal-orthogonal parametric (ROP) transform. By exploiting the properties of the ROP transform, we show that its independent parameters can successfully be used as an additional secret key for encryption. Experiments results carried clearly show the efficiency of the proposed encryption method.