A Comparative Analysis on Image Quality Assessment for Real Time Satellite Images

Rajkumar, S.; Malathi, G.

doi:10.17485/ijst/2016/v9i34/96766

Cited by 46 publications

(42 citation statements)

References 10 publications

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“…UACI is computed using equation (10) to determine the average intensity difference between the two images (OI and EI) [3,18,24]. UACI results are shown in Table 1 and it demonstrates that the proposed algorithm yields acceptable values.…”

Section: Unified Average Changed Intensity (Uaci)mentioning

confidence: 91%

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A Distinctive Afo Algorithm for Secured Medical Image Transmission Using Chaotic Crypto Technique

Tamilkodi¹,

Rama²

2019

IJARET

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The proposed system aims to develop a secure medical image encryption algorithm by combining chaotic map and cryptographic technique. In this paper, an innovative AFO (Arnold Cat Map, Fibonacci sequence and One Time Pad) algorithm for medical image encryption has been proposed. This AFO algorithm consists of four phases, in which diffusion, and confusion takes place two times. The pixels of the original (OI) and the key (KI) image are diffused by Arnold Cat Map first. Then the pixels of diffused images are confused with the help of Fibonacci sequence. Next, N unique random numbers are generated. Using these random numbers, the confused OI and KI image pixels are again permuted. The values of the resultant OI and KI pixels are pooled by utilizing the Vernam Cipher (also known as One Time Pad) in the final confusion phase. The quality of the reconstructed and an encrypted images are evaluated by some of the most widely used objective measures like MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio), AD (Average Difference), MD (Maximum Difference), MAE (Mean Absolute Error), (CC) Correlation Coefficient, IF (Image Fidelity), SSIM (Structural Similarity Index Metrics). Results of these measures commends that the proposed AFO encryption algorithm is suitable for secure medical image transmission.

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Section: Unified Average Changed Intensity (Uaci)mentioning

confidence: 91%

“…Number of Pixel Change Rate (NPCR) and Unified Average Changed Intensity (UACI) are the two image quality metrics used widely to measure the strength of an encryption algorithm against the differential attack. The value of these metrics will be zero, if both the original and an encrypted image are same [3,18,24].…”

Section: Differential Analysismentioning

confidence: 99%

A Distinctive Afo Algorithm for Secured Medical Image Transmission Using Chaotic Crypto Technique

Tamilkodi¹,

Rama²

2019

IJARET

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“…Kata steganografi berasal dari bahasa Yunani yakni steganos dan graphein, steganos memiliki makna disembunyikan sedangkan graphein bermakna menulis [1]. Steganografi disebut sebagai seni dan ilmu menyembunyikan informasi (pesan) ke dalam sebuah media dengan suatu tehnik sehingga tidak ada seorangpun yang mengetahui atau menyadari adanya pesan rahasia di dalam media tersebut, selain pengirim pesan dan penerima pesan yang memiliki kunci yang sama [2].…”

Section: Pendahuluanunclassified

Studi Steganografi Pada Citra Digital Menggunakan Shuffled Singular Value Decomposition (SSVD)

Aziza

Imah

2019

LIMITS

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AbstrakSteganografi merupakan suatu teknik untuk menyisipkan pesan tersembunyi ke dalam suatu citra. Steganografi memiliki peranan penting dalam hal penyembunyian informasi pada suatu komunikasi rahasia. Berbagai penelitian mengenai teknik steganografi telah dikembangkan, salah satu diantaranya menggunakan Singular Value Decomposition (SVD). Metode SVD cukup populer diperbincangkan dalam berbagai teknik di antaranya adalah steganografi dan penyisipan tanda air. Selain SVD terdapat pula sebuah metode yang dipercaya mampu memberikan hasil yang lebih baik dari SVD pada teknik penyisipan tanda air yakni Shuffled Singular Value Decomposition (SSVD). Perbedaan antara SSVD dan SVD terletak pada proses rekonstruksi yang diaplikasikan sebelum menerapkan SVD. Kepopuleran SSVD pada teknik penyisipan tanda air membuat penulis tertarik untuk mengusulkan studi teknik steganografi menggunakan SSVD. Data yang digunakan berupa dua buah citra RGB dan sebuah pesan berupa citra RGB. Kualitas citra diukur menggunakan PSNR dan Koefisien Korelasi. Dari uji coba diperoleh hasil bahwa kualitas penyisipan pesan yang telah dilakukan untuk kedua metode ini tergolong dalam kategori cukup baik yakni diatas 40 dB, sedangakan proses rekonstruksi pada pesan rahasia pada saat menggunakan metode SSVD mengakibatkan pesan yang disisipkan tidak mudah dibaca sehingga pesan yang disisipkan lebih aman daripada tanpa menggunakan proses rekonstruksi. AbstractSteganography is a technique of inserting hidden messages into an image. Steganography has an important role, in the field of information hiding for secret communication. Much recent research on it has been developed by, one of them is Singular Value Decomposition (SVD). SVD is quite popular discussed on various techniques including steganography and watermarking. Besides SVD, there is also a method that is believed to be able to provide better results than SVD on watermarking techniques, called Shuffled Singular Value Decomposition (SSVD). The differences between SSVD and SVD is on the shuffle process, which applied before applying the SVD. The popularity of SSVD on the watermarking technique made the writers interested in proposing a study of steganographic techniques using SSVD. The data used are two original RGB images and a message RGB image. Image quality is measured using the PSNR and Correlation Coefficient. The experimental result shows that the quality of insertion message which applied for both of these methods is categorized as quite good which is above 40 dB while shuffling process on the secret message causes the secret message not being easily readable so that the inserted message is securer than without using the shuffle process.

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“…It is castoff to identify the extent of nearness among two digitized images effectively. It reveals that greater value of SC indicates the deprived quality of image [15]. The value for SC is evaluated for two images are expressed in Eq.…”

Section: Structural Content (Sc)mentioning

confidence: 99%

An Experimental Exploration of Segmentation Techniques for Modi Script

Solanki¹,

Ingle²

2019

IJCA

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The segregation of image is most significant phase to identify borderline information of an image effectively. As various degradation exists in an image such as distorted pixel value, blurring in an image, poor luminance etc that affects the visual representation of an image. Using segmentation techniques, we attempts to improve the content of an image and make it clear for representation. There exist various edges and clustering based segmentation techniques such as perwitt, roberts, canny, sobel and K-means clustering that assist in segregating distortion information from a Modi character image to great extent. The comparative analysis of these segmentation techniques based on some performance parameters is performed to segment Modi character components. As a result, K-means clustering technique shows more appropriate outcome for segregating Modi numerals efficiently.

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A Comparative Analysis on Image Quality Assessment for Real Time Satellite Images

Cited by 46 publications

References 10 publications

A Distinctive Afo Algorithm for Secured Medical Image Transmission Using Chaotic Crypto Technique

A Distinctive Afo Algorithm for Secured Medical Image Transmission Using Chaotic Crypto Technique

Studi Steganografi Pada Citra Digital Menggunakan Shuffled Singular Value Decomposition (SSVD)

An Experimental Exploration of Segmentation Techniques for Modi Script

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