scholarly journals Perbaikan Citra Digital dengan Menggunakan Filtering Technique dan Similarity Measurement

d'CARTESIAN ◽  
2013 ◽  
Vol 2 (2) ◽  
pp. 1
Author(s):  
Gybert Saselah ◽  
Winsy Weku ◽  
Luther Latumakulita
Keyword(s):  
Digital Image ◽  
Gaussian Noise ◽  
Digital Images ◽  
Wiener Filter ◽  
Reduction Process ◽  
Input Image ◽  
Similarity Measurement ◽  
Gaussian Filter ◽  
Original Image ◽  
Noise Filter

Abstract Often the digital image can be contaminated with noise,  which usually occurs in the process of retrieval or storage of digital images and delivery process either via satellite or  cable . By using the technique of filtering noise reduction process will be performed on a digital image that has previously been given Gaussian noise and followed by a Similarity Measurement to identify similarities between  image filtered and original image. This study was conducted to determine the appropriate filtering techniques to reduce the Gaussian noise. Image processing in this study composed by the input image and read the image matrix, converting images, adding noise, denoising digital images by applying filters performed using Matlab R2012a software ( version 7.14.0.739) . Application of Gaussian filter with a value of = 1.0 produce a digital image that is closest to the original image than the application of a Gaussian filter with another value, for  . As for the application of the Wiener filter is seen that the greater the value, the resulting digital image will be closer to the original image. For further research can be done on other types of noise or to a combination of two or more noise. Keywords : Digital Image , Noise , Filter , Similarity Measurement. Abstrak Seringkali citra digital dapat terkontaminasi derau (noise), yang biasanya terjadi pada proses pengambilan ataupun penyimpanan citra digital serta proses pengiriman citra digital baik melalui satelit maupun melalui kabel juga. Dengan menggunakan teknik filtering akan dilakukan proses pengurangan noise pada suatu citra digital yang sebelumnya telah diberi Gaussian noise dan dilanjutkan dengan Similarity Measurement untuk mengidentifikasi kesamaan citra digital hasil filtering dengan citra original. Penelitian ini dilakukan untuk menentukan teknik filtering yang tepat untuk mengurangi Gaussian noise. Proses pengolahan citra dalam penelitian ini terdiri dengan proses input gambar dan membaca matriks citra, konversi citra, menambahkan noise, denoising citra digital dengan menerapkan filter yang dilakukan dengan menggunakan software Matlab R2012a (versi 7.14.0.739). Penerapan Gaussian filter dengan nilai = 1,0 menghasilkan citra digital yang paling mendekati citra original dibandingkan dengan penerapan Gaussian filter dengan nilai  lain, dimana . Sedangkan untuk penerapan Wiener filter terlihat bahwa semakin besar nilai , maka citra digital yang dihasilkan akan semakin mendekati citra original. Untuk penelitian selanjutnya dapat dilakukan pada jenis noise lain ataupun untuk gabungan dua noise atau lebih. Kata kunci: Citra digital, Noise, Filter, Similarity Measurement

scholarly journals Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter

2020 ◽  
Vol 30 (1) ◽  
pp. 240-257
Author(s):  
Akula Suneetha ◽  
E. Srinivasa Reddy
Keyword(s):  
Image Quality ◽  
Mean Square Error ◽  
Fuzzy Set ◽  
Digital Image ◽  
Gaussian Noise ◽  
Digital Images ◽  
Structural Similarity ◽  
Fuzzy Rules ◽  
Mean Square ◽  
Image Edges

Abstract In the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters (median filter, Gaussian filter, fuzzy filter, etc.) have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges while removing noise. In this paper, a modified fuzzy set filter has been proposed to eliminate noise for restoring the digital image. Usually in fuzzy set filter, sixteen fuzzy rules are generated to find the noisy pixels in the digital image. In modified fuzzy set filter, a set of twenty-four fuzzy rules are generated with additional four pixel locations for determining the noisy pixels in the digital image. The additional eight fuzzy rules ease the process of finding the image pixels,whether it required averaging or not. In this scenario, the input digital images were collected from the underwater photography fish dataset. The efficiency of the modified fuzzy set filter was evaluated by varying degrees of Gaussian noise (0.01, 0.03, and 0.1 levels of Gaussian noise). For performance evaluation, Structural Similarity (SSIM), Mean Structural Similarity (MSSIM), Mean Square Error (MSE), Normalized Mean Square Error (NMSE), Universal Image Quality Index (UIQI), Peak Signal to Noise Ratio (PSNR), and Visual Information Fidelity (VIF) were used. The experimental results showed that the modified fuzzy set filter improved PSNR value up to 2-3 dB, MSSIM up to 0.12-0.03, and NMSE value up to 0.38-0.1 compared to the traditional filtering techniques.

Gaussian Noise Filter Using Variable Step Time Matrix of PCNN

2011 ◽  
Vol 48-49 ◽  
pp. 551-554 ◽  
Author(s):  
Yuan Yuan Cheng ◽  
Hai Yan Li ◽  
Qi Xiao ◽  
Yu Feng Zhang ◽  
Xin Ling Shi
Keyword(s):  
Gaussian Noise ◽  
Spatial Information ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Wiener Filter ◽  
Noise Filter ◽  
Variable Step ◽  
Mean Filter ◽  
Reduction Methods ◽  
Novel Method

A novel method was brought forward for the purpose of filtering Gaussian noise effectively by using variable step time matrix of the simplified pulse coupled neural network (PCNN). Firstly, the time matrix of PCNN, related to the grayscale and spatial information of an image, is calculated to identify the noise polluted pixels. Subsequently, a variable step, a long step for strong noise and a short step for weak noise, based on the time matrix is applied to modify the grayscale of noised pixels in a sliding window. And then wiener filter is used to the image to further filter the noise. Experiments show that the proposed filter can remove Gaussian noise effectively than other noise reduction methods such as median filter, mean filter, wiener filter etc, and the filtered image is smooth and the details and edges are sharp. Compared with existing PCNN based Gaussian noise filter, the proposed filter gets higher Peak Signal-to-Noise Ratio (PSNR) and better performance.

Digital image post processing techniques for taxonomic publications with reference to insects

2020 ◽  
Vol 12 (1) ◽  
pp. 15173-15180
Author(s):  
Nikhil Joshi ◽  
Hemant Ghate ◽  
Sameer Padhye
Keyword(s):  
Digital Image ◽  
Digital Images ◽  
Original Image ◽  
Post Processing ◽  
Taxonomic Information ◽  
Processing Techniques

There exists substantial literature for capturing digital images of insect specimens for taxonomy purposes but very few papers are available on post processing of these images.  We present a few techniques for editing digital images of insects using Adobe® Photoshop® which can be performed in a relatively short amount of time.  The results clearly show that techniques using a combination of options like Curves, Dodge/Burn, Hue/Saturation and Lab Color mode in the software, enhance the quality of the original image without changing any taxonomic information.  These methods applied in different combinations can be used for taxonomy of any insect taxon.  We also caution the readers of the abuse of such techniques in context of taxonomy. 

Robust Watermarking Method using QIM with VSS for Image Copyright Protection

2021 ◽  
Vol 2021 (1) ◽  
pp. 28-40
Author(s):  
Minh Thanh Tạ
Keyword(s):  
Digital Image ◽  
Secret Sharing ◽  
Copyright Protection ◽  
Digital Images ◽  
Experimental Results ◽  
Watermark Image ◽  
Original Image ◽  
Visual Secret Sharing ◽  
Robust Watermarking ◽  
Copyright Information

This paper proposes a new watermarking method for digital image by composing the DWT-QIM based embedding with visual secret sharing (VSS) method. Firstly, the watermark image is separated into $n$ shares by using the $k-out-of-n$ method, called $(k,n)$ visual secret sharing. One of share is employed in order to embed into the original image for copyright protection. Another $(n-1)$ of shares are registered with Vietnam Copyright Department. When the dispute happens, the verifier can extract the watermark information from the watermarked image, then, decode it with $(k-1)$ shares chosen from $(n-1)$ shares to achieve the copyright information. Our experimental results show that our proposed method works efficiently on the digital images.

scholarly journals A DENOISING OF BIOMEDICAL IMAGES

2015 ◽  
Vol XL-5/W6 ◽  
pp. 73-78 ◽  
Author(s):  
D. N. H. Thanh ◽  
S. D. Dvoenko
Keyword(s):  
Image Quality ◽  
Total Variation ◽  
Digital Image ◽  
Gaussian Noise ◽  
Digital Images ◽  
Poisson Noise ◽  
Biomedical Images ◽  
Biomedical Image ◽  
Digital Devices ◽  
Imaging Science

Today imaging science has an important development and has many applications in different fields of life. The researched object of imaging science is digital image that can be created by many digital devices. Biomedical image is one of types of digital images. One of the limits of using digital devices to create digital images is noise. Noise reduces the image quality. It appears in almost types of images, including biomedical images too. The type of noise in this case can be considered as combination of Gaussian and Poisson noises. In this paper we propose method to remove noise by using total variation. Our method is developed with the goal to combine two famous models: ROF for removing Gaussian noise and modified ROF for removing Poisson noise. As a result, our proposed method can be also applied to remove Gaussian or Poisson noise separately. The proposed method can be applied in two cases: with given parameters (generated noise for artificial images) or automatically evaluated parameters (unknown noise for real images).

scholarly journals MENDETEKSI ORISINALITAS CITRA DIGITAL DENGAN MENERAPKAN METODE ADLER-32

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Jelita Lahagu
Keyword(s):  
Digital Image ◽  
Digital Images ◽  
Image Data ◽  
Original Image ◽  
Image Content ◽  
Human Eye ◽  
Object Based

The development of digital images is now very rapid, where the processing of image data, documents on digital images make images easily created or manipulated easily, even without leaving a visual imprint for users to manipulate an image. The ease in making and changing an image can damage the credibility of the originality / authenticity of the image in various aspects.Image is a combination of points, lines, shapes and colors to create an imitation of an object. Based on this, the pixel changes the original image so that it does not indicate the original image or the image has been manipulated. Thus the detection of the image can be known the authenticity of an image using the Adler-32 Algorithm.  Small changes of pixels do not make the image content detected by the human eye. This is explained in pixels like the long width in the image. The basis of this research is to detect the originality or authenticity of a digital image. Keywords : Image, Originality, Manipulation, Adler-32

scholarly journals PENGAMANAN CITRA DIGITAL BERDASARKAN MODIFIKASI ALGORITMA RC4

2018 ◽  
Author(s):  
Taronisokhi Zebua
Keyword(s):  
Digital Image ◽  
Digital Images ◽  
Initial Vector ◽  
The Internet ◽  
Original Image ◽  
Secret Image ◽  
Encryption And Decryption ◽  
Pixel Value ◽  
Cryptographic Techniques

Digital images of a private and confidential very extend to wiretapping by other parties, especially when the image is distributed over the internet. The tapping or misuse of the confidential private image, of course, harm the image owner. One technique to minimize the above measures is the utilization of cryptographic techniques. Cryptography techniques can secure digital images by modifying the image pixel values so that the resulting image is different from the original image. An RC4 algorithm can be used in realizing the purpose of cryptographic technique. But this algorithm has a weakness where the solving of this algorithm with know plaintext attack or know ciphertext only can be done easily. This research describes the security of digital images based on RC4 algorithm modification. The modification is to add an initial vector block in the process of encryption and decryption and shift a number of bits in a certain position. The result of this research is a digital image with pixel values that are much different from the original pixel value to make it difficult for others in manipulating the secret image

Authentication of Digital Image using Exif Metadata and Decoding Properties

2018 ◽  
pp. 335-341 ◽  
Author(s):  
D. P. Gangwar ◽  
Anju Pathania
Keyword(s):  
Digital Image ◽  
Digital Images ◽  
Software Tools ◽  
Robust Analysis

This work presents a robust analysis of digital images to detect the modifications/ morphing/ editing signs by using the image’s exif metadata, thumbnail, camera traces, image markers, Huffman codec and Markers, Compression signatures etc. properties. The details of the whole methodology and findings are described in the present work. The main advantage of the methodology is that the whole analysis has been done by using software/tools which are easily available in open sources.

PERBANDINGAN METODE MD4 DAN SHA 384 UNTUK MENDETEKSI ORISINALITAS CITRA DIGITAL

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Lemcia Hutajulu ◽  
Hery Sunandar ◽  
Imam Saputra
Keyword(s):  
Digital Image ◽  
Detrimental Effect ◽  
Digital Images ◽  
Computer Crime ◽  
The Other ◽  
Image Manipulation ◽  
The Internet ◽  
Secret Key

Cryptography is used to protect the contents of information from anyone except those who have the authority or secret key to open information that has been encoded. Along with the development of technology and computers, the increase in computer crime has also increased, especially in image manipulation. There are many ways that people use to manipulate images that have a detrimental effect on others. The originality of a digital image is the authenticity of the image in terms of colors, shapes, objects and information without the slightest change from the other party. Nowadays many digital images circulating on the internet have been manipulated and even images have been used for material fraud in the competition, so we need a method that can detect the image is genuine or fake. In this study, the authors used the MD4 and SHA-384 methods to detect the originality of digital images, by using this method an image of doubtful authenticity can be found out that the image is authentic or fake.Keywords: Originality, Image, MD4 and SHA-384

scholarly journals Digital Graphic Documentation and Architectural Heritage: Deformations in a 16th-Century Ceiling of the Pinelo Palace in Seville (Spain)

2021 ◽  
Vol 10 (2) ◽  
pp. 85
Author(s):  
Juan Reinoso-Gordo ◽  
Antonio Gámiz-Gordo ◽  
Pedro Barrero-Ortega
Keyword(s):  
20Th Century ◽  
Digital Image ◽  
Digital Images ◽  
Laser Scanner ◽  
16Th Century ◽  
Southern Europe ◽  
Architectural Heritage ◽  
Digital Documentation ◽  
First Time

Suitable graphic documentation is essential to ascertain and conserve architectural heritage. For the first time, accurate digital images are provided of a 16th-century wooden ceiling, composed of geometric interlacing patterns, in the Pinelo Palace in Seville. Today, this ceiling suffers from significant deformation. Although there are many publications on the digital documentation of architectural heritage, no graphic studies on this type of deformed ceilings have been presented. This study starts by providing data on the palace history concerning the design of geometric interlacing patterns in carpentry according to the 1633 book by López de Arenas, and on the ceiling consolidation in the 20th century. Images were then obtained using two complementary procedures: from a 3D laser scanner, which offers metric data on deformations; and from photogrammetry, which facilitates the visualisation of details. In this way, this type of heritage is documented in an innovative graphic approach, which is essential for its conservation and/or restoration with scientific foundations and also to disseminate a reliable digital image of the most beautiful ceiling of this Renaissance palace in southern Europe.

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