Lena Image Research Articles

Well-posedness for a fourth order nonlinear equation related to image processing

Using the entropy estimates in Min et al. (2013), we establish the global existence and uniqueness of solutions to a fourth order equation related to image processing. Some numerical results on the Lena image are also presented to show the effectiveness of the equation for noise removal.

High-Efficiency Customized Coarse-Grained Dynamically Reconfigurable Architecture for JPEG2000

This brief presents an efficient implementation of JPEG2000 encoding algorithm based on an architecture consisting of a coarse-grained dynamically reconfigurable instruction cell array and an embedded advanced RISC machine core. In this implementation, different tasks within the JPEG2000 encoding algorithm are allocated with proper computational resources to achieve high throughput. The proposed architecture is dynamically reconfigured for different tasks during the encoding process. Simulation results demonstrate that the proposed architecture provides a throughput of up to 52.1 f/s (or 19.18 ms/frame) to encode a 256 × 256 standard Lena test image. Compared with various digital signal processor & very long instruction word-based JPEG2000 solutions, the proposed architecture provides significant advantages in terms of throughput and energy consumption.

Omnidirectional antireflection polymer films nanoimprinted by density-graded nanoporous silicon and image improvement in display panel

We present a low-cost method to fabricate large-area polycarbonate AR nanostructures to improve the luminous intensity and image clarity of a commercial 2.0-inch display panel in bright condition. The polycarbonate AR nanostructures were nanoimprinted by the graded-density nanoporous silicon template with nanoparticle-catalyzed etching. The average reflectivity of the AR film in visible wavelength region was reduced from 10.2% to 4.8% in the optimized case. After attaching on the display panel to reduce the light reflection on the substrate, the brightness enhancement and decrease of ambient light reflection were observed. Due to the enhancement of contrast ratio, the quality index of the Lena image test was improved from 0.85 to 0.92 under strong ambient illumination.

Edge detection using ACO and F ratio

Edge detection is an important step for finding the discontinuities of images and detecting the boundaries of objects. This work presents a novel algorithm for image edge detection using ant colony optimization and Fisher ratio (F ratio)-based techniques. Ants generally search the food from the nest to the food source in the way that maximizes the intensity of pheromone (a chemical secretion). The proposed technique considers that the movements of the artificial ants are steered by the local intensity variation in the image pixel. The directions of ants movements in the image are determined using a direction probability matrix, computed by pheromone and heuristic information of possible directions. In this work, F ratio technique is utilized to determine the optimum threshold value from updated pheromone matrix. This threshold value is further used to extract binary edge map from pheromone matrix. The experiment is conducted on the different test images, i.e., Cameraman, Lena, Coins, Peppers, House and Pillsetc image. The proposed edge detection algorithm is evaluated on the basis of statistical parameters such as kappa, figure of merit, Baddeley’s delta metric and Hausdorff distance, and the experimental results show that the proposed method performs better as compared to earlier reported techniques in most of the cases.

A Robust Secondary Secure Communication Scheme Based on Synchronization of Spatiotemporal Chaotic Systems

This paper deals with the synchronization of spatiotemporal chaotic systems and presents a new robust secondary chaotic secure communication system for digital signal transmissions which can recover digital signal even though the transmitted signal is influenced by limited noise. The transmitter terminal and the receiver terminal both contain a spatiotemporal chaotic system and a hyperchaotic system. The asymptotic convergence of the errors between the states of the transmitter terminal and the receiver terminal has been proved based on the Lyapunov stable theory and active-passive decomposition (APD) method. Moreover, a random digital signal and a binary Lena image are encrypted and decrypted successfully to verify the efficiency of the proposed robust secure communication system.

Improved anisotropic diffusion filtering for SAR image despeckling

In synthetic aperture radar (SAR) images, the speckle noise often corrupts salient information that is of interest (e.g. textures, small hard targets, object boundaries, etc.). To tackle such an issue, proposed is a novel anisotropic diffusion filter that manages to simultaneously fulfil competing requirements: noise reduction on homogeneous regions, weak edges preservation, and keeping hard targets intact. The capabilities of the proposed filter were proved by comparing it with another two non-linear diffusion filters applied on a Lena image corrupted by a multiplicative speckle noise and on a real SAR image acquired by the Cosmo-SkyMed satellite constellation.

Intellectual property right protection of image data using DCT and spread spectrum-based watermarking

For digital image, watermarking provides intellectual property right protection through embedded copyright mark. However, due to attacks using signal processing methods offers challenges in designing robust copyright techniques. This paper presents a novel method for enhancing robustness in copyright marking into mid-frequency discrete cosine transform DCT coefficients of an image using spread spectrum techniques. Performance evaluation of proposed algorithm has been made using bit error rate BER and peak signal to noise ratio PSNR value for different watermark size and images: Lena, Girl, and Tank images yield similar results. This algorithm is simple and does not require the original cover image for watermark recovery. A set of systematic experiments, including JPEG compression, Gaussian filtering and addition of noise are performed to prove robustness of our algorithm. Thus, it is potentially useful in robust copy-right marking for intellectual property right protection applications.

A Study on Edge Marking Scheme of Various Standard Edge Detectors

This paper presents a study on edge marking scheme of various standard edge detectors viz. Sobel, Prewitt, Roberts, Laplacian of Gaussian (LoG) and Canny. On the basis of edge map obtained for a synthetic rectangular board image, obtained from five edge detectors, suggests classifying the detectors in three categories namely, pre-marker, post-marker and mixed-marker. Pratt’s figure of merit (PFOM) is used as a quantitative evaluation criterion for the above mentioned classification. Experimental results obtained for Lena and Parrot image provides convincing results to establish proposed classification. General Terms Image Processing

An Improved Reversible Data Hiding in Encrypted Images Using Side Match

This letter proposes an improved version of Zhang's reversible data hiding method in encrypted images. The original work partitions an encrypted image into blocks, and each block carries one bit by flipping three LSBs of a set of pre-defined pixels. The data extraction and image recovery can be achieved by examining the block smoothness. Zhang's work did not fully exploit the pixels in calculating the smoothness of each block and did not consider the pixel correlations in the border of neighboring blocks. These two issues could reduce the correctness of data extraction. This letter adopts a better scheme for measuring the smoothness of blocks, and uses the side-match scheme to further decrease the error rate of extracted-bits. The experimental results reveal that the proposed method offers better performance over Zhang's work. For example, when the block size is set to 8 8, the error rate of the Lena image of the proposed method is 0. 34%, which is significantly lower than 1.21% of Zhang's work.

A Hybrid Wavelet-Based Restoration Method for Agricultural Images

To improve denoising results for agricultural images, a hybrid wavelet-based method of agricultural image denoising was developed that was inspired by the idea of crossbreeding in living beings and the crossover operator in genetic algorithms. This method hybridized the advantages of two individual image-denoising methods using the crossover and mutation operators. The noisy image was denoised via wavelet thresholding and by applying an additional filter (such as a Wiener filter or a median filter), and the two denoised images were called the male and female parents. Next, the two parents were transformed into the encoding space to form the chromosomes. Then, the chromosomes were selected via the fitness function using the selection and crossover rates for the crossover and mutation operators. After several generations of crossover and mutation operations, the superior offspring was obtained. Finally, the offspring was decoded as an image with better noise removal results. The effectiveness of this proposed algorithm was tested using both agricultural images (wheat and apple) and a non-agricultural image (Lena). The experimental results indicated that this new denoising algorithm achieved better performance than conventional denoising methods in terms of visual quality and peak signal-to-noise ratio (PSNR). The original PSNR values of the three images were 59.22, 59.63, and 59.67 dB, whereas the PSNR values were 73.26 and 71.62 dB for the wheat and apple images using the hybrid wavelet-average method, and the PSNR was 70.94 dB for the Lena image using the hybrid wavelet-median method. It can be assumed that this new algorithm could also be applied to other agricultural images with good performance.

Image Vector Quantization codec indexes filtering

Vector Quantisation (VQ) is an efficient coding algorithm that has been widely used in the field of video and image coding, due to its fast decoding efficiency. However, the indexes of VQ are sometimes lost because of signal interference during the transmission. In this paper, we propose an efficient estimation method to conceal and recover the lost indexes on the decoder side, to avoid re-transmitting the whole image again. If the image or video has the limitation of a period of validity, re-transmitting the data wastes the resources of time and network bandwidth. Therefore, using the originally received correct data to estimate and recover the lost data is efficient in time-constrained situations, such as network conferencing or mobile transmissions. In nature images, the pixels are correlated with their neighbours and VQ partitions the image into sub-blocks and quantises them to the indexes that are transmitted; the correlation between adjacent indexes is very strong. There are two parts of the proposed method. The first is pre-processing and the second is an estimation process. In pre-processing, we modify the order of code- vectors in the VQ codebook to increase the correlation among the neighbouring vectors. We then use a special filtering method in the estimation process. Using conventional VQ to compress the Lena image and transmit it without any loss of index can achieve a PSNR of 30.429 dB on the decoder. The simulation results demonstrate that our method can estimate the indexes to achieve PSNR values of 29.084 and 28.327 dB when the loss rate is 0.5% and 1%, respectively.

DCT Image Compression by Run-Length and Shift Coding Techniques.

The mathematical concept of a DCT transform is a powerful tool in many areas; it is also, served as an approach in image processing discipline. In this work an image is processed as three color channel. The correlated pixels values of an image can be transformed to a representation where its coefficients are de-correlated. The term "decorrelated" means that the transformed values are independent of one another. As a result, they can be encoded independently, which make it simpler to construct a statistical model. Correlated values are coded with run-length coding techniques while shift coding used to decode the DC term and the other five lifting values. In this work, we suggest to save the first five values from every block to keep it back without any significant errors.The obtained bit rates was extended to be within range (11.4 , 2.6), compression ratio (2.76 , 13.34 )the values of the fiedility parameters (PSNR) was within the range (31.61 , 46.21) for the lena test image in both sizes (128×128 and 256×256), and PSNR was calculated as average for the three color channels, red, green , blue

Miniaturization of grayscale images

Printing of binary patterns onto substrates has been the strength of resist-based binary lithography that has advanced the semiconductor industry. When patterning grayscale structures however, grayscale-lithography processes that are often difficult to use are considered. Here, we describe a process using binary-lithography to create arbitrary grayscale patterns. Particularly, we demonstrate a novel algorithm for the miniaturization of grayscale images that preserves grayscale information when imaged in a scanning electron microscope (SEM). The brightness level of each pixel was adjusted by controlling the density of nanometer-scale pixel elements. Using 17 shades of gray, we demonstrate the electron-beam lithography patterning of an M.C. Escher mezzotint and the Lena image with pixel elements consisting of 10-nm-diameter nanoposts spaced by gaps as small as 10 nm. The patterned images were tens of microns in size and faithfully reproduce the original images under SEM inspection. The process described could find applications in the fabrication of deep sub-wavelength elements with gradually varying dimensions in nanophotonic devices, and in creating grayscale images as anti-counterfeit features on substrates.

Analysis Of Spiht Algorithm For Satellite Image Compression

Wavelets offer an elegant technique for representing the levels of details present in an image. When an image is decomposed using wavelets, the high pass component carry less information, and vice-versa. The possibility of elimination of the high pass components gives higher compression ratio in the case of wavelet based image compression. To achieve higher compression ratio, various coding schemes have been used. Some of the well known coding algorithms are EZW (Embedded Zero-tree Wavelet), SPIHT (Set Partitioning in Hierarchical Tree) and EBCOT (Embedded Block Coding with Optimal Truncation). SPIHT has been one of the popular schemes used for image compression. In this paper the performance of the SPIHT (Set Partitioning in Hierarchical Trees) compression technique for satellite images are studied. The satellite rural and urban images have been used for the present analysis. The standard Lena image is used for the purpose of comparison. For a given compression ratio, the PSNR (peak signal to noise ratio) values are computed to evaluate the quality of the reconstructed image. The analysis carried out clearly suggests that the PSNR values increases with the level of decomposition. For the satellite images the PSNR values achievable are less compared to that of Standard Lena Image and the SPIHT Algorithm are better suited for compression of Satellite urban Images.

Efficient Color Transformations on Quantum Images

Efficient transformations on the color content of images using single qubit operations are proposed based on the Flexible Representation of Quantum Images (FRQI). Utilizing the single qubit dedicated for encoding color information in the FRQI representation, the proposed operations offer massive speed-up in terms of changes in the color information in comparison with classical ones. Simulations of the FRQI images and circuits of these transformations using synthetic and Lena images on classical computers demonstrate the feasibility of the proposal. Together with position related operations, the color transformations could provide the foundation to achieve practical applications which are inefficient at present.

Adaptive reversible data hiding scheme based on integer transform

In this paper, we present a new reversible data hiding algorithm based on integer transform and adaptive embedding. According to the image block type determined by the pre-estimated distortion, the parameter in integer transform is adaptively selected in different blocks. This allows embedding more data bits into smooth blocks while avoiding large distortion generated by noisy ones, and thus enables very high capacity with good image quality. For instance, by the proposed method, we can embed as high as 2.17 bits per pixel into Lena image with a reasonable PSNR of 20.71 dB. Experimental results demonstrate that the proposed method outperforms some state-of-the-art algorithms, especially for high capacity case.

Robust copyright marking using Weibull distribution

For multimedia document, watermarking provides many advantages; however, its vulnerability due to attacks using signal processing methods offers challenge in designing robust techniques. This paper presents a novel method for enhancing robustness in copyright marking into mid-frequency discrete cosine transform (DCT) coefficients of an image. We establish that Weibull distribution suitably models mid-frequency coefficients well and use it for hiding copyright data. Our method is robust against JPEG compression attacks at both high and low compressions. Further, it is statistically undetectable in comparison to existing techniques of data hiding based on DCT coefficients. This is because it insignificantly affects the DCT coefficients of the stego image without compromising with data hiding capacity of the host image. Simulation result on Lena, Gibbon, Boat, and Peppers images illustrates that our algorithm offers lower bit error rate ( BER) and higher peak signal to noise ratio ( PSNR) leading to improved imperceptibility. Thus, it is useful in robust copyright marking.

Visual simulation of retinal images through microstructures

The space distribution of photoreceptors is a main topic in artificial retina design procedures. A fundamental question is how different retina architectures reproduce the same image and which their properties are? This paper presents a new method to emulate the visual response of biological or artificial retinas. The proposed method can predict the vision output image of any retina with known photoreceptors distribution. A simple method is proposed that considers only two parameters to simulate the output image of any retina architecture: the distribution of the photoreceptors in the retina and the estimated light response of its photoreceptors. The distribution of the photoreceptors along the retina is modeled by geometrical figures that let define a set of many different outer trajectories. The paper discusses also a new method to organize the layout of any retinal architecture design using a set of basic square vertical phototransistors cells according with a previously defined photoreceptors distribution. The Lena image is used to predict the degree of resolution at the central area and how it is faded towards the periphery.

Image denoising based on adaptive fusion of curvelet transform and Total Variation

This paper proposed an adaptive denoising approach, which fuses the images denoised by Total Variation (TV), curvelet-based method and edge information. Edge information is extracted from the noise residue of TV method by processing it through curvelet transform. The denoising abilities of the proposed method are evaluated on standard Lena image as well as on brain Computed Tomography (CT) images. Experimental results show that the proposed approach reduces the staircase effect caused by TV method and also reduces fuzzy edges induced by curvelet transform in the homogeneous areas of the image. This proposed adaptive fusion-based approach gives superior results not only for noise suppression but also for edge preservation.

Image Super Resolution Based on Interpolation of Wavelet Domain High Frequency Subbands and the Spatial Domain Input Image

In this paper, we propose a new super-resolution technique based on interpolation of the high-frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The proposed technique uses DWT to decompose an image into different subband images. Then the high-frequency subband images and the input low-resolution image have been interpolated, followed by combining all these images to generate a new super-resolved image by using inverse DWT. The proposed technique has been tested on Lena, Elaine, Pepper, and Baboon. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques. For Lena's image, the PSNR is 7.93 dB higher than the bicubic interpolation.