Gray level image processing using contrast enhancement and watershed segmentation with quantitative evaluation

2008 ◽  
Author(s):  
Zhengmao Ye ◽  
Habib Mohamadian ◽  
Yongmao Ye
Keyword(s):  
Image Processing ◽  
Contrast Enhancement ◽  
Quantitative Evaluation ◽  
Gray Level ◽  
Watershed Segmentation ◽  
Gray Level Image

Empirical multiresolution models applicable to gray-level image processing

1997 ◽  
Vol 11 (2) ◽  
pp. 83-93
Author(s):  
María José García-Salinas ◽  
Juan Francisco Gómez-Lopera ◽  
Pedro Luis Luque-Escamilla ◽  
José Martínez-Aroza ◽  
Ramón Román-Roldán ◽  
...  
Keyword(s):  
Image Processing ◽  
Gray Level ◽  
Gray Level Image

scholarly journals Gray Level Image Contrast Enhancement Using Barnacles Mating Optimizer

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 169196-169214
Author(s):  
Shameem Ahmed ◽  
Kushal Kanti Ghosh ◽  
Suman Kumar Bera ◽  
Friedhelm Schwenker ◽  
Ram Sarkar
Keyword(s):  
Contrast Enhancement ◽  
Image Contrast ◽  
Gray Level ◽  
Image Contrast Enhancement ◽  
Gray Level Image

STEGANOGRAPHIC SCHEME FOR GRAY-LEVEL IMAGE USING PIXEL NEIGHBORHOOD AND LSB SUBSTITUTION

2010 ◽  
Vol 10 (04) ◽  
pp. 589-607 ◽  
Author(s):  
NAGARAJ V. DHARWADKAR ◽  
B. B. AMBERKER
Keyword(s):  
Image Processing ◽  
Secret Message ◽  
Gray Level ◽  
Embedding Capacity ◽  
Least Significant Bit ◽  
Secret Communication ◽  
Gray Level Image ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Lsb Substitution

The exchange of secret message using images has vital importance in secret communication. Steganographic scheme is employed to achieve the task of secret message communication using images. The existing scheme based on pixel value differencing (PVD) with least significant bit (LSB) sequential substitution suffer from low embedding capacity. The embedding capacity is increased by using the edge regions of image obtained by neighborhood connectivity of pixel. We propose an adaptive steganographic scheme for gray-level images. Our scheme relies on the neighborhood connectivity of pixels to estimate the embedding capacity and resolves the problem of sequential substitution by jumbling the bits of secret message. The effect of cropping and filtration attacks on stegoimage is minimized by embedding the copies of secret message into four different regions of the cover image. The performance of the scheme is analyzed for various types of image processing attacks like cropping, blurring, filtering, adding noise, and sharpening. The proposed scheme is found rigid to these attacks.

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