Modified integral imaging reconstruction and encryption using an improved SR reconstruction algorithm

Abstract

We propose a monospectral image encryption method in which the multispectral color image acquisition by using heterogeneous monospectral cameras. Because the captured monospectral elemental images (EIs) belongs to grayscale image, it is means that the captured EIs can be directly encrypted by the proposed encoding method. Subsequently, the linear cellular automata (CA) and hyperchaotic encoding algorithm are employed to encrypt the captured EIs. Different from previous methods, the proposed method can directly encrypt the multispectral color information rather than having to divide into three color channels (R, G and B), thereby, the proposed method can greatly reduce the encryption calculation. MonospectralEIs encrypted by linear CA and hyper-chaotic system 2.2.1. M-sequence generated by linear CA CA can offer significant benefit over existing algorithms [33,34]. In a one-dimensional (1D), two-state, three-site neighbourhood CA, where the next state of a cell is updated according to its neighborhood, the value of each cell is 0 or 1. The value of each cells can be generated by a specified rule. The value of next state is calculated by the Boolean function with three parameters.where s i (t + 1) denotes the value of cell i at time t + 1, s i (t) denotes the value of the cell i at time t, y i−1 (t) is the the left neighboring cell value at time t, s i+1 (t) is the right neighboring cell value at time t, and F () represents the Boolean function defining a specified rule. According his theory of Wolfram, for the 2-state, 3-site CA, it has 2 8 rules. The Wolfram rules are defined from 0 to 255. Among the rules, eight Wolfram rules are linear. They are 0, 60, 90, 102, 150, 170, 204, and 240, respectively. The eight Wolfram linear rules are represented as follows:Rule 0 : s i (t + 1) = 0, Rule 60 : s i (t + 1) = s i−1 (t) ⊕ s i (t), Rule 90 : s i (t + 1) = s i−1 (t) ⊕ s i+1 (t), Rule 102 : s i (t + 1) = s i (t) ⊕ s i+1 (t), Rule 150 : s i (t + 1) = s i−1 (t) ⊕ s i (t) ⊕ s i+1 (t), Rule 170 : s i (t + 1) = s i−1 (t), Rule 204 : s i (t + 1) = s i (t), Rule 240 : s i (t + 1) = s t−1 (t).

Performance Evaluation of Tourism Human Resource Management Based on Fuzzy Data Mining

“…where • and ⊙ represent inner product and outer product in fuzzy operation, respectively [30][31][32].…”

Image Encryption Using Josephus Problem and Filtering Diffusion

“…Recently, researchers have developed many image security technologies such as information hiding [5], digital watermarking [6] and image encryption [7]- [10]. Among these technologies of protecting image, the image encryption is a visual and efficient technology that encrypts a meaningful image to be an unrecognized cipherimage [11]- [13]. Only using the correct key, one can recover the original image.…”

Cryptanalysis and Enhancement of an Image Encryption Scheme Based on Bit-Plane Extraction and Multiple Chaotic Maps

“…Digital image is one of the most popular information media among multiple multimedia representation forms because of its impressive advantages, such as intuitive nature, rich content, low cost and rapid transmission. However, there exist many security risks in the network transmission of digital images, such as interception, malicious falsification and illegal destruction by adversaries, which may lead to immeasurable but unperceived losses [2]- [4]. Therefore, ensuring secure transmission of digital images has become an important concern of every person living with cyberspace.…”