位相画像をアンラッピングする演算方法について
조회 수: 14 (최근 30일)
이전 댓글 표시
位相画像を読み込み,画像と二次元hanningフィルタを周波数領域で演算し,位相画像とフィルタ処理された画像を差分することで位相ラップを除去する方法をコード化しました.
しかし,自作フィルタの演算法やフィルタ処理後のcomplexの扱いが悪いのか元画像と変化がなく,位相のアンラッピングができません.
とくに周波数空間におけるlow-pass filteringが違うのではないかと考えています.
圧縮されたデータを貼り付けていますので非常に見苦しいかと存じますが,何卒ご教示頂ければ幸いです.
%% 位相画像読み込み
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2086.92488231161 2038.39852967719 2070.18266761303 2103.62745633442 2117.77597345645 2228.10090434365 2453.26313408208 2032.66444997210 1946.27781428234 1978.75323565025 2179.83192529460 2080.03834765055 2045.00657330197 1971.74012829992 1964.71289027971 2141.49537931010 1942.45201648213 1905.27842542762 2073.13160484750 2028.66437734384 2045.00118817366 2042.53948644293 1883.85850681271 2014.65182892955 1705.00558162807 1866.82040124410 2299.80203413637 2274.03895657510 2154.85557320621 1872.03569256887 1939.01058712183 1975.26514902757
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[km, kn] = size(alldata);
%% 位相画像を周波数空間へ格納
J = fft2(alldata); %画像に対して 2次元FFT (周波数領域 0 ~ 2*pi)
J = fftshift(J); % 周波数領域を-pi~piとする (中央に)
figure(1), imagesc(20*log10(abs(J))) % パワースペクトル表示
%% フィルタの作成
Kernelsize = 8;
w0 = hanning(Kernelsize)*hanning(Kernelsize)'; % Hanningフィルタ:任意サイズ作成
w = zeros(km, kn);
w((km-Kernelsize)/2:(km+Kernelsize)/2-1, (km-Kernelsize)/2:(km+Kernelsize)/2-1) = w0;
% フィルタ処理
filtered_J = J.*w; % フィルタ処理 (周波数空間フィルタリング)
filtered_J = ifftshift(ifft2(filtered_J)); % 周波数領域を 0 ~ 2*pi に戻す,IFFT処理で空間領域へ変換
figure(2), imagesc(abs(filtered_J))
%% フィルタ処理された演算画像出力
Phase = alldata-filtered_J;
figure(4),imagesc(abs(Phase)) % フィルタ後の画像表示
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