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Implementation of measure of relative tendency to phase image filtering spacial based
Syakrani N.a, Baskoro E.T.a, Mengko T.L.R.a, Suksmono A.B.a
a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]Complex image can split to magnitudo and phase images. The phase of complex function is uniquely defined only in the principal or wrapped value range (-π, π]. Complex image is producted by special equipment as MRI, InSAR and Optics. Image acquisition has noise mostly. The noise come from modality, transmission media or object of image. Generally, the noise has two classification that are additive as Gaussian or multiplicative as speckle. The noise make image processing effectiveless. One of measure of relative tendency in Statistics is quartile consist of low, middle (median) and upper quartiles. Until now, basic spatial filtering method is constructed mean based that linear category or median based that simple nonlinear category. There is different formulation to get measure of central or relatif tendency between magnitudo and phase data. This paper propose a new filtering method base on quartile to phase image specially. Using 3×3 window to implementation of quartile algorithm in Matlab is tested to simulation phase image named Peak2XY by two kind of noises that are Gaussian and Speckle. For example, PSNR of upper quartile filtering to Peak2XY by Gaussian noise with mean =0, variance=0.01, are LoQu = +20.2622; MidQu = +23.7045; UpQu = +21.3528. The quartile filtering method also tested to head phase image of Magnetics Resonance Imaging and Fuji of InSAR phase image. © 2014 AIP Publishing LLC.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Complex functions,Filtering method,Linear categories,noise,Phase image,PSNR,Spatial filtering methods,Transmission media[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]noise,phase image,PSNR,quartile filtering method[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1063/1.4868770[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]