Aerial Image Quality Research Articles

Mathematical Model of Enhanced Aerial Image Quality and Security through Wavelet-Based Dynamic Range Compression and Watermarking Techniques

This research introduces a novel wavelet-based dynamic range compression system tailored for improving the visual quality of digital photographs taken in high dynamic range environments with non-uniform lighting. Primarily designed for aerial photography in defense and security applications, this method excels in preserving local contrast and tonal rendition while efficiently managing dynamic range, making it highly suitable for aviation industry video streaming. A key advancement of this research is the development of an algorithm capable of enhancing aerial images to a quality that surpasses direct human observation in terms of clarity and robustness. Additionally, the research presents an innovative watermarking technique utilizing Local Binary Patterns (LBP) and Discrete Wavelet Transform (DWT). This approach employs the LBP operator in conjunction with wavelet approximation coefficients to generate a resilient binary watermark. The focus is on establishing more reliable watermarking methods to ensure enhanced security and resilience of embedded information. The study explores the application of public watermarking to facilitate easy access and comprehension of copyright and patent information, highlighting the technology's efficacy in protecting sensitive image data. The research further investigates the enhancement of neural network performance in watermarking applications using Gray Level Co-occurrence Matrix (GLCM) and Principal Component Analysis (PCA) algorithms. PCA is utilized for image selection, while GLCM aids in feature extraction from the original image. The performance of the PCA algorithm is assessed based on its implementation's scaling factor.Through simulations, the proposed algorithm demonstrated impressive results, especially in terms of Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), and correlation coefficients, confirming its potential in improving image quality and security in aerial photography and related applications. This study represents a significant advancement in the fields of image processing and digital security, offering new tools and methodologies for enhancing the quality and protection of aerial imagery.

Improvement of aerial image by simulations

We measured the contrast of standard charts using two different types of retro-reflectors in an AIRR (Aerial imaging by retro-reflection) system, and examined the results to be reproduced by optical simulation. As a result, it became possible to reproduce the effect of retro-reflector diffraction on the Aerial image quality of the AIRR system by optical simulation.

RANDOM NOISE ASSESSMENT IN AERIAL AND SATELLITE IMAGES

Abstract. Random noise in aerial and satellite images is one of the factors, decreasing their quality. The noise level assessment in images is paid not enough attention. The method of numerical estimation of random image noise is considered. The object of the study is the image noise estimating method, based on harmonic analysis. The capability of using this method for aerial and satellite image quality assessment is considered. The results of the algorithm testing on model data and on real satellite images with different terrain surfaces are carried out. The accuracy estimating results for calculating the root-mean-square deviation (RMS) of random image noise by the harmonic analysis method are shown.

Применение открытых баз данных снимков при оценке изобразительного качества материалов аэрофотосъемки для целей картографирования

An aerial image quality assessment for mapping purposes using open image databases is carried out. While using methods based on reference images, it is a generally adopted practice to use open databases, designed to provide researchers with reference data, i.e. shots whose quality can be accepted as a reference. Such databases are widely used to test the efficiency of methods and algorithms for assessing and improving photographic quality. The possibility of applying this approach for aerial photography assessment in terms of visual properties is shown. The values of fine quality indicators for reference sample of open image library LIVE Database are determined

Inter/intra-category discriminative features for aerial image classification: A quality-aware selection model

Classification, recognition, and quality assessment of aerial images strongly depends on detecting and identifying their discriminative visual features. In practice, aerial images provide clues for various applications, including disaster prediction, automatic navigation, and military target detection. However, the detection of discriminative cues in aerial images is quite problematic since the aerial image quality is susceptible to luminance and noise, while aerial images have significantly different topological structures. We propose a novel method to explore quality-related and topological cues from aerial images for visual classification to mitigate these problems. We first decompose aerial images into several components, each being processed via the morphological filtering. Subsequently, we leverage the quality model to generate discriminative regions and topologies. Each aerial image is represented using a feature vector extracted from these regions. Afterward, we train a CNN-based visual classification model to predict aerial image categories. Experimental results have shown that our method can effectively predict aerial image categories, and the proposed algorithm is more robust than other state-of-the-art ones.

Mining discriminative spatial cues for aerial image quality assessment towards big data

Evaluating massive-scale aerial/satellite images quality is useful in computer vision and intelligent applications. Traditional local features-based algorithms have achieved impressive performance. However, spatial cues, i.e., geometric property and topological structure, have not been exploited effectively and explicitly. Thus, in this paper, we propose a novel method for image quality assessment towards aerial/satellite images, where discriminative spatial cues are well encoded. More specifically, in order to mine inherent spatial structure of aerial images, each image is segmented into several basic components such as buildings, airport and playground. Afterwards, a weighted region adjacency graph (RAG) is built based on the basic components to represent the spatial feature of each aerial image. We integrate the spatial feature with other transform domain features, and train a support vector regression model to achieve image quality assessment. Experiments demonstrate that our method shows competitive or even better performance compared with several state-of-the-art algorithms.

Placement of Sub-Resolution Assist Features Based on a Genetic Algorithm

Resolution enhancement techniques compatible with an ArF (193 nm) immersion optical lithography system may constitute an effective means of minimizing the size of technology nodes of the dynamic random access memory. This paper investigated one such technique, namely mask optimization (MO), and applied sub-resolution assist features (SRAFs) in the MO to improve the aerial image quality of a target pattern that had undergone optical proximity correction (OPC). This paper first developed an optical model based on the Hopkins model to create an interference map, which was then used to create a cut-level map. The cut-level map was instrumental in predicting potential SRAF sites and randomly generating SRAFs that would serve as the initial population for a genetic algorithm (GA). Chromosomes were defined as a section map and encoded genes were used to define SRAF and target pattern. Using a GA to identify SRAF geometric measurements and placement was revealed to increase the process window and improve the image performance of the target pattern. This paper used 1D and 2D line/space (L/S) images as the baseline to test the convergence of the proposed method. 2D images were also used to test improvements in aerial image performance. The results indicated that the 1D L/S pattern converged at the 100th iteration. Furthermore, the depths of the focus of the 2D L/S array and 2D contact hole patterns were successfully increased by 113 and 21 nm, respectively. The proposed SRAF method, which integrated the GA and interference map, was able to ensure the diversity of potential SRAF solutions. Moreover, it was able to restrict the SRAF solutions to rectangular structures through the application of mask rules, thereby reducing the cost and improving the feasibility of photomasks.

Optimization of resist parameters to improve the profile and process window of the contact pattern in advanced node

Typically, the printing of contact patterns uses a dark-field (DF) mask in combination with a positive tone resist and positive tone development (PTD) process. PTD, which has a mature process and simulation model, had been widely applied in high-volume manufacturing. For the low aerial image quality of a DF mask in advanced node, PTD is substituted by negative tone development (NTD), which uses a positive tone resist and bright-field mask. Due to the high cost and immature simulation model of NTD process, it is worthwhile to extend PTD to some critical patterns. With the purpose of improving the resist profile and process window (PW) of the contact pattern with a PTD process in advanced node, an optimization method combined with the idea of a genetic algorithm is put forward. For performance of the optimized resist under the conditions of best focus and best dose, an evaluation based on the through pitch square contact patterns with the critical dimension (CD) fixed at 50 nm has been provided. The generalization performance of the optimized resist is also analyzed by a systematic method, which contains the resist profile and PW simulation on the base of through CD and through pitch contact patterns. The above simulation results verify the effectiveness and validity of the proposed optimization method.

Ant Colony Optimization-Based Freeform Sources for Enhancing Nanolithographic Imaging Performance

As the complexity of mask patterns increases, the standard off-axis illumination in 193-nm immersion systems is increasingly becoming inadequate for high-quality lithography. In this study, a source optimization (SO) technique was employed for improving lithographic resolution. A pixel-based optimization process was developed for constructing freeform sources on a PC platform to enhance contrast and improve process window (PW). In the proposed SO algorithm, the metaheuristic binary ant colony optimization algorithm was applied for constructing the freeform sources. Moreover, the proposed algorithm converged to the optimal solution between the 300th and 400th iterations. The performance of this algorithm was assessed using the half pitch (hp) 45-nm line/space (L/S) and 55-nm SRAM contact hole (CH) patterns. The fitness function was quality of aerial image, exposure latitude (EL), and depth of focus (DOF); the constructed freeform sources enhanced the contrast and extended the PW for the patterns. The DOF increased from 0.91 to 1.1 μm and 0.042 to 0.061 μm for the L/S and SRAM CH patterns, respectively, at an EL of 5% when using the freeform source. Moreover, the freeform source improved the mask error enhancement factor by 22% for the SRAM pattern.

Different aerial image formation into two directions by crossed-mirror array

Different aerial images in two directions can be formed by using a crossed-mirror array (CMA). The array is composed of reflective imaging elements based on dihedral corner mirrors and is used to form an aerial LED image. However, as CMA is formed from one-sided mirrors for keeping down the cost, only two of the four aperture walls of CMA are mirrors and the other two are back sides of the mirrors. As a dihedral corner mirror needs double reflections, aerial image quality varies with the incidence direction of light on the CMA. In this paper, we propose a new CMA configuration for forming aerial images in two directions more clearly. Clear different aerial images in two directions can be successfully formed by using the new CMA configuration.

基于全变分的航空图像条带噪声消除方法

Stripe noise perturbs image qualities of push-broom-type aerial camera, thus eliminating stripe noise is of vital importance to improve the precision of posterior data analysis. The main sources and the model of stripe noise in aerial images are analyzed and a new destriping stripe noise algorithm based on total variation is proposed. The gain and offset of each pixel are estimated based on quasi-homogeneous regions. The total variation algorithm is utilized and the image is reconstructed by the gradient descent method iteratively. The qualitative analysis results demonstrate that the peak signal-to-noise ratio of the simulated image is improved from 31 dB to 40 dB and the improvement factor of radiometric quality of the real aerial image is improved to 9 dB. Compared with traditional methods, the proposed algorithm can achieve higher inverse coefficient of variation and improvement factors of radiometric quality. Stripe noise can be effectively removed with detailed information of the original image reserved.

Pursuit of Lower Critical Dimensional Uniformity in EUV Resists

This paper describes Dow’s efforts toward improved Critical Dimensional Uniformity (CDU) in EUV resists. Many non-material related factors contribute to good CDU, such as aerial image quality. We have focused on fundamental resist properties like intrinsic dissolution contrast and we have found that the photo-decomposable base (PDB) concept can be successfully employed. With the use of a PDB, we can reduce CDU variation at lower exposure energies. For sensitivity, we have focused on more efficient EUV photon capture through increased EUV absorption, as well as more highly efficient PAGs for greater acid generating efficiency. The formulation concepts will be confirmed using Prolith stochastic resist modeling. For the 26nm hp contact holes, we observe excellent overall process window with over 280nm depth of focus for a 10% exposure latitude Process window. The 1σ CDU is 1.1 nm. We also obtain 20nm hp contact resolution in one of our new EUV resists.

Negative Tone Imaging Process and Materials for EUV Lithography

The advantages of NTI process in EUV is demonstrated by optical simulation method for 0.25NA and 0.33NA illumination system with view point of optical aerial image quality and photon density. The extendabLlity of NTI for h igher NA system is considered for further tight pitch and small size contact hole imaging capability. Process and material design strategy to NTI were discussed with consideration on comparison to ArF NTI process and materials, and challenges in EUV materials dedicated to NTI process were discussed as well. A new polymer was well designed for EUV-NTD process, and the resists formulated with the new polymer demonstrated good advantage of resolution and sensitivity in isolated trench imaging, and 24 nm half pitch resolution at dense C/H, with 0.3NA MET tool.

Mask roughness impact on extreme UV and 193nm immersion lithography

The contribution of mask absorber line edge roughness on printed resist lines is studied for extreme UV and 193nm immersion lithography. Programmed roughness modules were designed for roughness transfer function evaluation on 88nm pitch line space patterns. The tested modules were designed applying variations of roughness amplitude and spatial frequency. Power spectral density analysis was performed on top-down SEM images. The effect of frequency roughness filtering by the lithographic optical system was studied with different illumination settings. It was found that, except for the degradation of the aerial image due to the filtering effect, less performing illuminations show an increased deterioration of the aerial image quality and thus contribute further to line edge roughness. A comparison with previous work was completed on different mask architectures and photoresist platforms. Resist performance can attenuate the roughness transfer from mask but at the cost of worse chemical gradient at the edges of the exposed regions.

Wavefront-based pixel inversion algorithm for generation of subresolution assist features

The generation of subresolution assist features (SRAFs) using inverse-lithography techniques demands extensive computational resources which limits its deployment in advanced CMOS nodes. In this paper, we propose a wavefront-based pixel inversion algorithm to quickly obtain inverse masks with a high aerial image quality. Further assisted by a flexible pattern simplification technique, we present effective SRAF generation and placement based on the calculated inverse mask. The proposed approach can be easily inserted prior to a conventional mask correction flow for subsequent concurrent optimizations of both drawn patterns and SRAFs. The innovative pixel inversion and pattern simplification techniques allow quality mask corrections as produced by inverse lithography while maintaining the convenience of standardized/validated process flows currently used in the industry.

Circular apertures for contact hole patterning in 193 nm immersion lithography

Contact hole patterning has always been one of the most challenging issues in lithography. Conventional optical proximity correction (OPC) approach for contact hole patterning involves dimensional biasing, addition of serifs at corners, and insertion of subresolution enhancement features. However, as dimensions reduce, process window enhancement resulted from conventional OPC approach encounters limitations. In this paper, a new approach for contact hole patterning is investigated. Instead of using a square shape as target of a printed feature, a circular shape is proposed. Using the proposed method improvement in aerial image quality is achieved and the average improvement in the depth of focus is around 11%. In addition, the average normalized image logarithmic slope improvement for different pitches is found to be around 15%.

Finding optimum value of numerical aperture for the best aerial image quality

Optimization of lithographic process plays a pivotal role in modern fabrication. Many parameters are engaged in optimizing optical systems used in lithographic process. In this paper, we show with a fixed rule for resolution enhancement techniques (RETs) we have an optimum value for image quality by definition of figure of merit (FOM). We find out how we are close to replicate a desired target mask on photoresist and derive an analytical formula for FOM versus numerical aperture (NA). The effect of variation in NA on quality of image that will be on photoresist is also shown.

COMPARATIVE ANALYSIS OF AUTOMATIC DIGITAL IMAGE BALANCING AND STANDARD HISTOGRAM ENHANCEMENT TECHNIQUES IN REMOTE SENSING IMAGERY

Recently, radiometric image homogenization techniques have been thoroughly studied among the digital mapping techniques. The main characteristics of digital image balancing methods ⎯ vignetting and hot spot minimization, as well as color homogenization ⎯ were inherited from photo laboratory techniques. However, the current digital image balancing processing uses mathematical modeling of matrices which evaluates the most suitable histogram templates and applies customized corrections to each image region, with or without user intervention. In this paper, we review the main phenomena involved in aerial image quality and outine image correction. Image balancing problems and solutions will focus on digital processing techniques and their applications. The study will also apply an automatic recursive block method and a standard histogram technique to sattelite imagery. The balancing and color adjustment performances are compared.

High-Absorption Resist Process for Extreme Ultraviolet Lithography

The trade-off relationships among resolution, sensitivity, and line edge roughness (LER) have been the most serious problem for the realization of extreme ultraviolet (EUV) lithography. The enhancement of polymer absorption in combination with an ultrathin resist process is a solution for the trade-off problem. In this study, the relationship between aerial images of incident photons and latent images generated by polymer deprotection in high-absorption resists was investigated by a simulation based on the EUV sensitization mechanisms. Because of the restricted acid diffusion length, the side wall degradation is a problem at 22 nm fabrication. The improvement of aerial image quality significantly improves the side wall profiles. The relationship between the acid generator concentration and latent image quality was also investigated in terms of side wall angle and LER. By increasing the acid generator concentration from 10 to 30 wt %, the extent of LER can be reduced by ∼17%.

General framework for parameter optimization in imaging interferometric lithography

Imaging interferometric lithography (IIL) employs the resolu- tion enhancement technique (RET) of off-axis illumination (OAI) to over- come the spatial frequency resolution limitations that are imposed by the band limitedness of a conventional optical lithography system. IIL im- proves upon the aerial image resolution of a conventional optical lithog- raphy system by providing a wavelength division multiplexing approach toward the attainment of the maximum spatial frequency coverage of 2/l, which is independent of the numerical aperture of the optical system. IIL combines OAI, which provides access to higher spatial frequencies of the mask, with multiple exposures and several different configurations of the polarization parameters, the frequency parsing parameters, and the exposure energy ratios are possible. Although experiments detailing the resolution enhancement capabilities of IIL in isolated parameter settings exist, a unified approach toward parameter optimization in IIL that would enable automated software for TCAD is presently lacking. With the objec- tive of providing a framework for parameter optimization in IIL, we pro- pose in this paper, an approach that encompasses: (a) polarization di- versity in the different on-axis or off-axis exposures of IIL, (b) an aggregate error metric for evaluating aerial image quality, (c) a block- based optimization process that incorporates the proposed error metric on representative, smaller blocks of the mask, (d) an optimization pro- cess that determines the optimal parameter settings for the entire mask using the lessons learned from the blocks. This framework for optimiza- tion of parameters in IIL enables comparison of IIL with other contempo- rary RETs and also enables the study and analysis of hybrid approaches such as combinations of IIL with optimal proximity correction. Simulation results that demonstrate the efficacy of the IIL-based approach and re- inforce its capabilities as a viable RET for subwavelength optical lithog- raphy are presented. © 2005 Society of Photo-Optical Instrumentation Engineers.