scholarly journals Effect of Geometric Sharpness on Translucent Material Perception

2019 ◽  
Author(s):  
Bei Xiao ◽  
Shuang Zhao ◽  
Ioannis Gkioulekas ◽  
Wenyan Bi ◽  
Kavita Bala
Keyword(s):  
Optical Properties ◽  
Similarity Index ◽  
Human Perception ◽  
Structural Similarity ◽  
Target Object ◽  
Light Transport ◽  
Optical Parameters ◽  
Image Metrics ◽  
3D Geometry ◽  
Object Shapes

When judging optical properties of a translucent object, humans often look at sharp geometric features such as edges and thin parts. Analysis of the physics of light transport shows that these sharp geometries are necessary for scientific imaging systems to be able to accurately measure the underlying material optical properties. In this paper, we examine whether human perception of translucency is likewise affected by the presence of sharp geometry, by confounding our perceptual inferences about an object’s optical properties. We employ physically accurate simulations to create visual stimuli of translucent materials with varying shapes and optical properties under different illuminations. We then use these stimuli in psychophysical experiments, where human observers are asked to match an image of a target object by adjusting the material parameters of a match object with different geometric sharpness, lighting geometry, and 3D geometry. We find that the level of geometric sharpness significantly affects perceived translucency by the observers. These findings generalize across a few illuminations and object shapes. Our results suggest that the perceived translucency of an object depends on both the underlying material optical parameters and 3D shape. We also conduct analyses using computational metrics including (luminance-normalized) L2, structural similarity index (SSIM), and Michelson contrast. We find that these image metrics cannot predict perceptual results, suggesting low level image cues are not sufficient to explain our results.

Analysis of SSIM Based Quality Assessment across Color Channels of Images

2015 ◽  
pp. 1233-1245
Author(s):  
T. Chandrakanth ◽  
B. Sandhya
Keyword(s):  
Image Processing ◽  
Quality Assessment ◽  
Color Space ◽  
Similarity Index ◽  
Human Perception ◽  
Structural Similarity ◽  
Subjective Assessment ◽  
Color Images ◽  
Color Spaces ◽  
Cie Lab

Advances in imaging and computing hardware have led to an explosion in the use of color images in image processing, graphics and computer vision applications across various domains such as medical imaging, satellite imagery, document analysis and biometrics to name a few. However, these images are subjected to a wide variety of distortions during its acquisition, subsequent compression, transmission, processing and then reproduction, which degrade their visual quality. Hence objective quality assessment of color images has emerged as one of the essential operations in image processing. During the last two decades, efforts have been put to design such an image quality metric which can be calculated simply but can accurately reflect subjective quality of human perception. In this paper, the authors evaluated the quality assessment of color images using SSIM (structural similarity index) metric across various color spaces. They experimented to study the effect of color spaces in metric based and distance based quality assessment. The authors proposed a metric using CIE Lab color space and SSIM, which has better correlation to the subjective assessment in a benchmark dataset.

scholarly journals Image Text Deblurring Method Based on Generative Adversarial Network

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 220
Author(s):  
Chunxue Wu ◽  
Haiyan Du ◽  
Qunhui Wu ◽  
Sheng Zhang
Keyword(s):  
Similarity Index ◽  
Human Perception ◽  
Specific Area ◽  
Structural Similarity ◽  
Wasserstein Distance ◽  
Generative Adversarial Networks ◽  
Natural Image ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Adversarial Networks

In the automatic sorting process of express delivery, a three-segment code is used to represent a specific area assigned by a specific delivery person. In the process of obtaining the courier order information, the camera is affected by factors such as light, noise, and subject shake, which will cause the information on the courier order to be blurred, and some information will be lost. Therefore, this paper proposes an image text deblurring method based on a generative adversarial network. The model of the algorithm consists of two generative adversarial networks, combined with Wasserstein distance, using a combination of adversarial loss and perceptual loss on unpaired datasets to train the network model to restore the captured blurred images into clear and natural image. Compared with the traditional method, the advantage of this method is that the loss function between the input and output images can be calculated indirectly through the positive and negative generative adversarial networks. The Wasserstein distance can achieve a more stable training process and a more realistic generation effect. The constraints of adversarial loss and perceptual loss make the model capable of training on unpaired datasets. The experimental results on the GOPRO test dataset and the self-built unpaired dataset showed that the two indicators, peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), increased by 13.3% and 3%, respectively. The human perception test results demonstrated that the algorithm proposed in this paper was better than the traditional blur algorithm as the deblurring effect was better.

Analysis of SSIM based Quality Assessment across Color Channels of Images

2015 ◽  
Vol 4 (3) ◽  
pp. 30-42 ◽  
Author(s):  
T. Chandrakanth ◽  
B. Sandhya
Keyword(s):  
Image Processing ◽  
Quality Assessment ◽  
Color Space ◽  
Similarity Index ◽  
Human Perception ◽  
Structural Similarity ◽  
Subjective Assessment ◽  
Color Images ◽  
Color Spaces ◽  
Cie Lab

Advances in imaging and computing hardware have led to an explosion in the use of color images in image processing, graphics and computer vision applications across various domains such as medical imaging, satellite imagery, document analysis and biometrics to name a few. However, these images are subjected to a wide variety of distortions during its acquisition, subsequent compression, transmission, processing and then reproduction, which degrade their visual quality. Hence objective quality assessment of color images has emerged as one of the essential operations in image processing. During the last two decades, efforts have been put to design such an image quality metric which can be calculated simply but can accurately reflect subjective quality of human perception. In this paper, the authors evaluated the quality assessment of color images using SSIM (structural similarity index) metric across various color spaces. They experimented to study the effect of color spaces in metric based and distance based quality assessment. The authors proposed a metric using CIE Lab color space and SSIM, which has better correlation to the subjective assessment in a benchmark dataset.

ANALISIS SENSITIVITAS VIDEO MPEG-4 BERDASARKAN STRUKTUR FRAME PADA TRANSMISI DVB-T

2020 ◽  
Vol 25 (2) ◽  
pp. 86-97
Author(s):  
Sandy Suryo Prayogo ◽  
Tubagus Maulana Kusuma
Keyword(s):  
Deep Learning ◽  
Bit Error Rate ◽  
Error Rate ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Signal To Noise ◽  
Structural Similarity Index ◽  
Noise Ratio

DVB merupakan standar transmisi televisi digital yang paling banyak digunakan saat ini. Unsur terpenting dari suatu proses transmisi adalah kualitas gambar dari video yang diterima setelah melalui proses transimisi tersebut. Banyak faktor yang dapat mempengaruhi kualitas dari suatu gambar, salah satunya adalah struktur frame dari video. Pada tulisan ini dilakukan pengujian sensitifitas video MPEG-4 berdasarkan struktur frame pada transmisi DVB-T. Pengujian dilakukan menggunakan simulasi matlab dan simulink. Digunakan juga ffmpeg untuk menyediakan format dan pengaturan video akan disimulasikan. Variabel yang diubah dari video adalah bitrate dan juga group-of-pictures (GOP), sedangkan variabel yang diubah dari transmisi DVB-T adalah signal-to-noise-ratio (SNR) pada kanal AWGN di antara pengirim (Tx) dan penerima (Rx). Hasil yang diperoleh dari percobaan berupa kualitas rata-rata gambar pada video yang diukur menggunakan metode pengukuran structural-similarity-index (SSIM). Dilakukan juga pengukuran terhadap jumlah bit-error-rate BER pada bitstream DVB-T. Percobaan yang dilakukan dapat menunjukkan seberapa besar sensitifitas bitrate dan GOP dari video pada transmisi DVB-T dengan kesimpulan semakin besar bitrate maka akan semakin buruk nilai kualitas gambarnya, dan semakin kecil nilai GOP maka akan semakin baik nilai kualitasnya. Penilitian diharapkan dapat dikembangkan menggunakan deep learning untuk memperoleh frame struktur yang tepat di kondisi-kondisi tertentu dalam proses transmisi televisi digital.

scholarly journals GPR B-Scan Image Denoising via Multi-Scale Convolutional Autoencoder with Data Augmentation

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1269
Author(s):  
Jiabin Luo ◽  
Wentai Lei ◽  
Feifei Hou ◽  
Chenghao Wang ◽  
Qiang Ren ◽  
...  
Keyword(s):  
Image Denoising ◽  
Data Augmentation ◽  
Noise Suppression ◽  
Random Noise ◽  
Similarity Index ◽  
Structural Similarity ◽  
Training Dataset ◽  
Generative Adversarial Network ◽  
Multi Scale ◽  
Convolutional Autoencoder

Ground-penetrating radar (GPR), as a non-invasive instrument, has been widely used in civil engineering. In GPR B-scan images, there may exist random noise due to the influence of the environment and equipment hardware, which complicates the interpretability of the useful information. Many methods have been proposed to eliminate or suppress the random noise. However, the existing methods have an unsatisfactory denoising effect when the image is severely contaminated by random noise. This paper proposes a multi-scale convolutional autoencoder (MCAE) to denoise GPR data. At the same time, to solve the problem of training dataset insufficiency, we designed the data augmentation strategy, Wasserstein generative adversarial network (WGAN), to increase the training dataset of MCAE. Experimental results conducted on both simulated, generated, and field datasets demonstrated that the proposed scheme has promising performance for image denoising. In terms of three indexes: the peak signal-to-noise ratio (PSNR), the time cost, and the structural similarity index (SSIM), the proposed scheme can achieve better performance of random noise suppression compared with the state-of-the-art competing methods (e.g., CAE, BM3D, WNNM).

scholarly journals Synthesis of PVA/CeO2 Based Nanocomposites with Tuned Refractive Index and Reduced Absorption Edge: Structural and Optical Studies

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1570
Author(s):  
Shujahadeen B. Aziz ◽  
Elham M. A. Dannoun ◽  
Dana A. Tahir ◽  
Sarkawt A. Hussen ◽  
Rebar T. Abdulwahid ◽  
...  
Keyword(s):  
Refractive Index ◽  
Optical Properties ◽  
Absorption Edge ◽  
Ceo2 Nanoparticles ◽  
Poly Vinyl Alcohol ◽  
Optical Parameters ◽  
Single Oscillator Model ◽  
Vis Spectroscopy ◽  
The Impact ◽  
Host Polymer

In the current study, polymer nanocomposites (NCPs) based on poly (vinyl alcohol) (PVA) with altered refractive index and absorption edge were synthesized by means of a solution cast technique. The characterization techniques of UV–Vis spectroscopy and XRD were used to inspect the structural and optical properties of the prepared films. The XRD patterns of the doped samples have shown clear amendments in the structural properties of the PVA host polymer. Various optical parameters were studied to get more insights about the influence of CeO2 on optical properties of PVA. On the insertion of CeO2 nanoparticles (NPs) into the PVA matrix, the absorption edge was found to move to reduced photon energy sides. It was concluded that the CeO2 nanoparticles can be used to tune the refractive index (n) of the host polymer, and it reached up to 1.93 for 7 wt.% of CeO2 content. A detailed study of the bandgap (BG) was conducted using two approaches. The outcomes have confirmed the impact of the nanofiller on the BG reduction of the host polymer. The results of the optical BG study highlighted that it is crucial to address the ɛ” parameter during the BG analysis, and it is considered as a useful tool to specify the type of electronic transitions. Finally, the dispersion region of n is conferred in terms of the Wemple–DiDomenico single oscillator model.

scholarly journals Polymer Composites with 0.98 Transparencies and Small Optical Energy Band Gap Using a Promising Green Methodology: Structural and Optical Properties

Polymers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1648
Author(s):  
Muaffaq M. Nofal ◽  
Shujahadeen B. Aziz ◽  
Jihad M. Hadi ◽  
Wrya O. Karim ◽  
Elham M. A. Dannoun ◽  
...  
Keyword(s):  
Refractive Index ◽  
Optical Properties ◽  
Polymer Composites ◽  
Amorphous Phase ◽  
Absorption Edge ◽  
Complex Form ◽  
Bandgap Energy ◽  
Optical Parameters ◽  
Visible Spectroscopy ◽  
Uv Visible

In this work, a green approach was implemented to prepare polymer composites using polyvinyl alcohol polymer and the extract of black tea leaves (polyphenols) in a complex form with Co2+ ions. A range of techniques was used to characterize the Co2+ complex and polymer composite, such as Ultraviolet–visible (UV-Visible) spectroscopy, Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). The optical parameters of absorption edge, refractive index (n), dielectric properties including real and imaginary parts (εr, and εi) were also investigated. The FRIR and XRD spectra were used to examine the compatibility between the PVA polymer and Co2+-polyphenol complex. The extent of interaction was evidenced from the shifts and change in the intensity of the peaks. The relatively wide amorphous phase in PVA polymer increased upon insertion of the Co2+-polyphenol complex. The amorphous character of the Co2+ complex was emphasized with the appearance of a hump in the XRD pattern. From UV-Visible spectroscopy, the optical properties, such as absorption edge, refractive index (n), (εr), (εi), and bandgap energy (Eg) of parent PVA and composite films were specified. The Eg of PVA was lowered from 5.8 to 1.82 eV upon addition of 45 mL of Co2+-polyphenol complex. The N/m* was calculated from the optical dielectric function. Ultimately, various types of electronic transitions within the polymer composites were specified using Tauc’s method. The direct bandgap (DBG) treatment of polymer composites with a developed amorphous phase is fundamental for commercialization in optoelectronic devices.

scholarly journals Microwave Imaging of Breast Skin Utilizing Elliptical UWB Antenna and Reverse Problems Algorithm

Micromachines ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 647
Author(s):  
Sameer Alani ◽  
Zahriladha Zakaria ◽  
Tale Saeidi ◽  
Asmala Ahmad ◽  
Muhammad Ali Imran ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Imaging System ◽  
Signal Transmission ◽  
Similarity Index ◽  
Structural Similarity ◽  
Microwave Imaging ◽  
Ultra Wideband ◽  
Uwb Antenna ◽  
System A ◽  
High Structural Similarity

Skin cancer is one of the most widespread and fast growing of all kinds of cancer since it affects the human body easily due to exposure to the Sun’s rays. Microwave imaging has shown better outcomes with higher resolution, faster processing time, mobility, and less cutter and artifact effects. A miniaturized elliptical ultra-wideband (UWB) antenna and its semi-spherical array arrangement were used for signal transmission and reception from the defected locations in the breast skin. Several conditions such as various arrays of three, six, and nine antenna elements, smaller tumor, multi-tumors, and skin on a larger breast sample of 30 cm were considered. To assess the ability of the system, a breast shape container with a diameter of 130 mm and height of 60 mm was 3D printed and then filled with fabricated skin and breast fat to perform the experimental investigation. An improved modified time-reversal algorithm (IMTR) was used to recreate 2D images of tumors with the smallest radius of 1.75 mm in any location within the breast skin. The reconstructed images using both simulated and experimental data verified that the system can be a reliable imaging system for skin cancer diagnosis having a high structural similarity index and resolution.

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