General Image Processing - Revision history

Kinoshita: /* Image Averaging */

2014-10-02T02:03:12Z

‎Image Averaging

Kinoshita: /* Image Averaging */

2014-10-02T02:03:00Z

‎Image Averaging

Kinoshita: /* Mathematical morphologyを使ったImage Processing */

2014-10-02T01:59:15Z

‎Mathematical morphologyを使ったImage Processing

Kinoshita: /* 実空間のKernelを用いたImage Processing */

2014-10-02T01:58:50Z

‎実空間のKernelを用いたImage Processing

Kinoshita: /* Fourier Spaceを利用したImage Processing */

2014-10-02T01:58:25Z

‎Fourier Spaceを利用したImage Processing

Kinoshita: /* Binarization */

2014-10-02T01:52:36Z

‎Binarization

Kinoshita: /* Edge extraction */

2014-10-02T01:52:03Z

‎Edge extraction

Kinoshita: /* Noise reduction */

2014-10-02T01:51:29Z

‎Noise reduction

Kinoshita: /* Quantization */

2014-10-02T01:09:47Z

‎Quantization

Kinoshita: /* Sampling */

2014-10-02T01:07:18Z

‎Sampling

← Older revision		Revision as of 02:03, 2 October 2014
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	== [[Image Averaging]] ==		== [[Image Averaging]] ==
−	If many images about the same photo field or the same particle exist, image averaging ~~raises~~ the quality of the images.	+	If many images about the same photo field or the same particle exist, image averaging can raise the quality of the images.

← Older revision		Revision as of 02:03, 2 October 2014
Line 50:		Line 50:

	== [[Image Averaging]] ==		== [[Image Averaging]] ==
−	~~the~~ same photo ~~fieldや同一粒子's imageがたくさんある場合には~~,~~画像の平均化を行うことで画像の質を上げることができます．~~	+	If many images about the same photo field or the same particle exist, image averaging raises the quality of the images.

@@ Line 47: / Line 47: @@
 == Image processing using the [[Kernel]] of the Real space ==
-== [[Mathematical morphology]]を使ったImage Processing ==
+== Image processing using the [[Mathematical morphology]] ==
 == [[Image Averaging]] ==
 　the same photo fieldや同一粒子's imageがたくさんある場合には,画像の平均化を行うことで画像の質を上げることができます．

@@ Line 45: / Line 45: @@
 　It is an useful method for an image which has repetition period.
-== 実空間の[[Kernel]]を用いたImage Processing ==
+== Image processing using the [[Kernel]] of the Real space ==
 == [[Mathematical morphology]]を使ったImage Processing ==

@@ Line 42: / Line 42: @@
 　This is the process of isolating the background and the signal, and extracting the representative point and the skeletal. And it is the start process of the analysis and image processing.
-== [[Fourier Space]]を利用したImage Processing ==
+== Image processing using the [[Fourier Space]] ==
-　繰り返し周期がある画像などでは有効な画像小胞です.
+　It is an useful method for an image which has repetition period.
 == 実空間の[[Kernel]]を用いたImage Processing ==

@@ Line 40: / Line 40: @@
 == [[Binarization]] ==
-　Signalと背景の切り分けや,代表点や骨格の抽出など,Image ProcessingやAnalysisのスタートとなる処理方法です.
+　This is the process of isolating the background and the signal, and extracting the representative point and the skeletal. And it is the start process of the analysis and image processing.
 == [[Fourier Space]]を利用したImage Processing ==

@@ Line 37: / Line 37: @@
 == [[Edge extraction]] ==
-　対象物の形を理解するために重要なステップですが,とても難しいステップでもあります.
+　This is an important step in order to understand the shape of the object, but it is also a very difficult step.
 == [[Binarization]] ==

@@ Line 18: / Line 18: @@
 == [[Noise reduction]] ==
-　Noiseが非常に多い画像を取り扱うためには,Noiseの性質をよく知ることが重要です.
+　In order to deal the image including a lot of noise, knowing well the nature of the noise is important.
-電子顕微鏡関係のNoiseとしては,下記に挙げるいくつかが想定されます.
+Show as following some factors about noise related to electron microscope.
-# 電子線量が少ないことから来る量子Noise:白色雑音(全域)
+# Quantum noise by lack of electron dose: White Noise(Whole field)
-# 電子のエネルギー損失と色収差からくる低分解能側に多く存在するNoise:有色雑音(全域)
+# Noise which exists many in the low-resolution side by energy lack of electron or chromatic aberration: Colored Noise(Whole field)
-# カメラのCCDや蛍光板,フィルムへの放射線,あるいは,ゴミなどによるNoise:局所雑音
+# Noise by radiation or dust on CCD, fluorescent screen, or film of camera: Local Noise
-などが挙げられます.
+and so on.
-　量子Noiseは,白色雑音の一種であり,ポアソン過程に従ったNoise分布をする場合が多いことが知られています.
+　Quantum Noise is one kind of White noise, and it is known that this is often noise distribution depending on Poisson Process.
-　非弾性散乱電子と色収差によるNoiseは,ぼけを伴い,低周波側に多く存在します.したがって,有色雑音となります.
+　In the low-resolution side There is noise by Inelastic scattered electrons or chromatic aberration,  with blur. Therefor, this noise is Colored.
-　カメラのCCDや蛍光板,フィルムへの放射線,あるいは,ゴミなどによる雑音は,局所雑音となるExampleです.宇宙線や蛍光板内の崩壊に起因する放射線によるものは,非常に高い輝度のPixelを与えます.CCD等の[[MTF]]のために,一点とはならず,ぼけを生じます.
+　Noise by radiation or dust on CCD, fluorescent screen, or film of camera is one example of Local Noise. Factor by cosmic rays or radiation by collapse of the fluorescent screen gives pixels which have considerable high contrast. Because of [[MTF]](e.g. by CCD), it is not one point, but occurs blur.
 === [[Smoothing]] ===
-　画像のもつNoiseを取り除くことを主たる目的として実施するImage Processing方法です.Noiseの性質をよく理解することで,適切なNoise除去が可能になります.
+　This is an image processing method with the primary purpose of eliminating the noise in the image. By understanding well the nature of the noise, the noise can be reduced properly.
 == [[Edge extraction]] ==

@@ Line 15: / Line 15: @@
 == [[Quantization]] ==
-　デジタルImage Processingでは,アナログである濃度値(光学密度)をあるビット数内で表現する量子化(ＡＤ変換)という操作が最初に必要です.ここで失ったInformationを取り戻す事は出来ません.
+　First, in digital image process the operation that expresses density values within certain number of bits (Optical density) is required. This operation is called quantization(AD convert). Information lost by this process can't be regained.
 == [[Noise reduction]] ==

@@ Line 12: / Line 12: @@
 == [[Sampling]] ==
-　アナログ画像をデジタル画像にするためには,空間をinterval,離散化することが重要です.このステップを標本化といいます.これに失敗すると,偽解像などの間違った画像を解釈する可能性があるので,注意が必要です.
+　To convert analog images to digital images, it is important that discretize the space by decomposing. This step is called Sampling. This failure might make incorrect interpretation like false image. Therefore, you must process carefully.
 == [[Quantization]] ==