Architecture of the discrete sosine transformation processor for image compression systems on the losless-to-lossy circuit

The hardware implementations of fixed-point DCT blocks, known as IntDCT [1] and BinDCT [2], require some solutions. One of the main issues is the choice between the implementation of the conversion on FPGA, or the implementation on a digital signal processor (Digital Signal Processor, DSP). Each of the implementations has its own pros and cons. One of the most important advantages of the DSP implementation is the presence of special instructions used in DSP, in particular, the ability to multiply two numbers in one clock cycle. Therefore, with the advent of DSP, the limitation on the number of multiplications in algorithms was removed. On the other hand, when implementing a block on an FPGA, we can limit not ourselves to the bitness of the data (within reasonable limits), we have the ability to parallelize all incoming data and implement specialized computing cores for various tasks. In fact, designing multimedia systems on FPGAs reminds the design of similar systems based on the logic of a small and medium degree of integration. Such an implementation has the same limitations: a relatively small amount of available memory, the need to design basic structural elements (multipliers, divisors), etc. It is the inequality of the addition and multiplication operations when they are implemented on FPGAs that caused the search for DCT algorithms with the smallest number of factors. However, even this is not enough, since the structure of the multiplier is many times more complex than the structure of the adder, which made it necessary to look for ways to transform without using multiplications at all. This article shows how, on the basis of integer direct and inverse DCT and distributed arithmetic, to create a new universal architecture of decorrelated transform on FPGAs without multiplication operations for image transformation coding systems that operate on the principle of lossless-to-lossy (L2L), and to obtain the best experimental results in terms of hardware resources compared to comparable compression systems.

Digital Watermarking using Grasshopper Optimization Algorithm

The advancement in computer science technology has led to some serious concerns about the piracy and copyright of digital content. Digital watermarking technique is widely used for copyright protection and other similar applications. In this paper, a technique for digital watermarking based on Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Grasshopper Optimization Algorithm (GOA) is proposed. The method computes the DWT of the cover image to obtain the sub-components of the image. The subcomponent is converted to frequency domain using DCT. The challenge is to find the optimal scaling factor to be used for watermarking. The authors have designed a GOA based technique that finds the optimized scaling factor and the coefficient for embedding the watermark. GOA makes the watermark undetectable and is invisible in the cover image. The watermark image is embedded in the cover image using these coefficients. The extraction of watermark from the cover image is done by using inverse DCT and DWT. The proposed method is compared with the other state of the art methods. The effectiveness of the proposed method is computed using Peak Signal to Noise Ratio (PSNR), Normalized Cross Correlation (NCC) and Image Fidelity (IF). The proposed method outperforms the other methods and can be effectively used for practical digital watermarking.

A hybrid OFDM–CDMA-based robust image watermarking technique

Digital watermarking is a process of embedding hidden information called watermark into different kinds of media objects. It uses basic modulation, multiplexing and transform techniques of communication for hiding information. Traditional techniques used are least significant bit (LSB) modification, discrete cosine transform (DCT), discrete wavelet transform (DWT), discrete Fourier transform (DFT), code division multiple access (CDMA) or a combination of these. Among these, CDMA is the most robust against different attacks except geometric attacks. This paper proposes a blind and highly robust watermarking technique by utilizing the basis of orthogonal frequency division multiplexing (OFDM) and CDMA communication system. In this scheme, the insertion process starts by taking DFT of host images, permuting the watermark bits in randomized manner and recording them in a seed as a key. Then PSK modulation follows inverse DFT (IDFT) that gives watermark information as OFDM symbols. These symbols are spread using spreading codes and then arithmetically added to the host image. Finally, scheme applies inverse DCT (IDCT) to get watermarked host images. The simulation results of the proposed scheme are compared with CDMA-based scheme in DCT domain. The results show that the robustness of the proposed scheme is higher than the existing scheme for non-geometric attacks.

Efficient Image Cipher Based on Baker Map in the Discrete Cosine Transform

This paper presents an efficient image cipher based on applying the chaotic Baker Map (BM) in the Discrete Cosine Transform (DCT). The encryption module of the proposed DCT-based BM image cipher employs a DCT on the original plain-image then, the DCT coefficients of the plain-image are shuffled with the BM. Finally, the inverse DCT is applied to the shuffled plain-image DCT coefficients to obtain the final cipher-image. The decryption module of the proposed DCT-based BM image cipher employs a DCT on the input cipher-image then, the DCT coefficients of the cipher-image are inversely shuffled with the BM. Finally, the inverse DCT is applied to the inversely shuffled cipher-image DCT coefficients to obtain the original plain-image. A set of experimental tests are performed to test the validity of the proposed DCT-based BM image cipher and the performed tests demonstrated the superiority of the proposed DCT-based BM image cipher in terms of statistical, differential, sensitivity and noise immunity.

All-in-Focused Image Combination in the Frequency Domain Using Light Field Images

All-in-focused image combination is a fusion technique used to acquire related data from a set of focused images at different depth levels, which suggests that one can determine objects in the foreground and background regions. When attempting to reconstruct an all-in-focused image, we need to identify in-focused regions from multiple input images captured with different focal lengths. This paper presents a new method to find and fuse the in-focused regions of the different focal stack images. After we apply the two-dimensional discrete cosine transform (DCT) to transform the focal stack images into the frequency domain, we utilize the sum of the updated modified Laplacian (SUML), enhancement of the SUML, and harmonic mean (HM) for calculating in-focused regions of the stack images. After fusing all the in-focused information, we transform the result back by using the inverse DCT. Hence, the out-focused parts are removed. Finally, we combine all the in-focused image regions and reconstruct the all-in-focused image.

A Fast DCT Algorithm for Watermarking in Digital Signal Processor

Discrete cosine transform (DCT) has been an international standard in Joint Photographic Experts Group (JPEG) format to reduce the blocking effect in digital image compression. This paper proposes a fast discrete cosine transform (FDCT) algorithm that utilizes the energy compactness and matrix sparseness properties in frequency domain to achieve higher computation performance. For a JPEG image of8×8block size in spatial domain, the algorithm decomposes the two-dimensional (2D) DCT into one pair of one-dimensional (1D) DCTs with transform computation in only 24 multiplications. The 2D spatial data is a linear combination of the base image obtained by the outer product of the column and row vectors of cosine functions so that inverse DCT is as efficient. Implementation of the FDCT algorithm shows that embedding a watermark image of 32 × 32 block pixel size in a 256 × 256 digital image can be completed in only 0.24 seconds and the extraction of watermark by inverse transform is within 0.21 seconds. The proposed FDCT algorithm is shown more efficient than many previous works in computation.