Semantic Driven Automated Image Processing Using the Concept of Colorimetry

Merugu, Suresh; Jain, Kamal

doi:10.1016/j.procs.2015.08.062

Cited by 8 publications

(4 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A third coordinate z can also be defined but is redundant since x+y+z=1 for all colors” as given in Ref. 27. x=XX+Y+Z,y=YX+Y+Z.x and y also have relation between RGB and XYZ, which is given as [XYZ]=[R G B][0.490000.310000.200000.176970.812400.010630.000000.010000.99000].“Thus the conversion from one color space to other can be done using above mentioned relations.…”

Section: Colorimetric Color Spacementioning

confidence: 99%

“…A third coordinate z can also be defined but is redundant since x þ y þ z ¼ 1 for all colors" as given in Ref. 27.…”

Section: Colorimetric Color Spacementioning

confidence: 99%

“…While linear spectral unmixing enables one to calculate the fractional abundances of various feature types, 6 , 8 it does not identify where about of these features within a subpixel. Hence, surrounding pixels likely belong to the same ground surface features 9 . During this assumption, subpixel-level representation improves spatial and spectral resolutions of resulting ground truth information.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, surrounding pixels likely belong to the same ground surface features. 9 During this assumption, subpixel-level representation improves spatial and spectral resolutions of resulting ground truth information.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Colorimetry-based edge preservation approach for color image enhancement

Merugu

Jain

2016

J. Appl. Remote Sens

Self Cite

View full text Add to dashboard Cite

Subpixel-based downsampling" is an approach that can implicitly enhance perceptible image resolution of a downsampled image by managing subpixel-level representation preferably with individual pixel. A subpixel-level representation for color image sample at edge region and color image representation is focused with the problem of directional filtration based on horizontal and vertical orientations using colorimetric color space with the help of saturation and desaturation pixels. A diagonal tracing algorithm and an edge preserving approach with colorimetric color space were used for color image enhancement. Since, there exist high variations at the edge regions, it could not be considered as constant or zero, and when these variations are random the need to compensate these to minimum value and then process for image representation. Finally, the results of the proposed method show much better image information as compared with traditional direct pixel-based methods with increased luminance and chrominance resolutions.

show abstract