Image enhancement (Nâng cao chất lượng hình ảnh)

Trường Cao Đẳng Nguyễn Tấấ t Thành Image Enhancement Ngành kỹ thuật y sinh Content  DSA  Dual energy  Gray scale transforms  Histogram transformation Digital subtraction angiography DSA = Dual energy  Những vật liệu khác có hệ sốấhấấ p thụ tia X khác nhaucó thể tạo ảnh từ nhiềề u m ức lượng khác  Điểm bấất lợi pp chụp nhiềề u lấề n với kV khác Dual energy     Dùng filter đốềng để tạo mức lượng khác Với tấấm đấều tiền cho qua toàn phổ tia X cách chụp X quang thống thường Tấấm thứ cho qua tia X lượng cao Xương cấấu trúc có canxi hấấp thu tia thành phấền X lượng thấấp tia X lượng cao qua mố có mật độ thấấp Dual energy Dual energy Gamma correction Gamma correction Some Typical Histograms • The shape of a histogram provides useful information for contrast enhancement Dark image Bright image Low contrast image High contrast image Histogram Equalization  Histogram equalization is a powerful point processing enhancement technique that seeks to optimize the contrast of an image at all points  As the name suggests, histogram equalization seeks to improve image contrast by flattening, or equalizing, the histogram of an image  In image processing, a histogram is a histogram of sample values  For an 8-bit image there will be 256 possible samples in the image and the histogram will simply count the number of times that each sample value actually occurs in the image  In other words, the histogram gives the frequency distribution of sample values within the image 23 Histogram Equalization  Histogram equalization is a way of improving the local contrast of an image without altering the global contrast  This method is especially useful in images having large regions of similar tone such as an image with a very light background and dark foreground  Histogram equalization can expose hidden details in an image by stretching out the contrast of local regions and hence making the differences in the region more pronounced and visible  Non-linear point processing technique that attempts to flatten the histogram such that there are equal numbers of each sample value in the image 24 Example Original image and its histogram Histogram equalized image and its histogram Example Example Histogram in MATLAB h = imhist (f, b) Where f, is the input image, h is the histogram, b is number of bins (tick marks) used in forming the histogram (b = 255 is the default) A bin, is simply, a subdivision of the intensity scale For example, if we are working with uint8 images and we let b = 2, then the intensity scale is subdivided into two ranges: – 127 and 128 – 255 the resulting histograms will have two values: h(1) equals to the number of pixels in the image with values in the interval [0,127], and h(2) equal to the number of pixels with values in the interval [128 255] Histogram in MATLAB  We obtain the normalized histogram simply by using the expression p = imhist (f, b) / numel(f) numel (f): a MATLAB function that gives the number of elements in array f (i.e the number of pixels in an image Other ways to display Histograms  Consider an image f The simplest way to plot its histogram is to use imhist with no output specified: >> imhist (f); Figure 3.7(a) shows the result Phấn vùng dựa vào tương tự vềềcường độ Kỹ thuật 1: Đặt ngưỡng (thresholding)  Ngưỡng đơn  Đa ngưỡng Tài liệu tham khảo  Biomedical image analysis [...]... for contrast enhancement Dark image Bright image Low contrast image High contrast image Histogram Equalization  Histogram equalization is a powerful point processing enhancement technique that seeks to optimize the contrast of an image at all points  As the name suggests, histogram equalization seeks to improve image contrast by flattening, or equalizing, the histogram of an image  In image processing,... corresponds to the dynamic range of the image and the height of each bar corresponds to the sample count or the probability  The spread of the histogram relates directly to image contrast where  narrow histogram distributions are representative of low contrast images  wide distributions are representative of higher contrast images 16 Histogram Example 17 Histogram Example The image is characterized by low... values  For an 8-bit image there will be 256 possible samples in the image and the histogram will simply count the number of times that each sample value actually occurs in the image  In other words, the histogram gives the frequency distribution of sample values within the image 23 Histogram Equalization  Histogram equalization is a way of improving the local contrast of an image without altering... value in the image 24 Example Original image and its histogram Histogram equalized image and its histogram Example Example Histogram in MATLAB h = imhist (f, b) Where f, is the input image, h is the histogram, b is number of bins (tick marks) used in forming the histogram (b = 255 is the default) A bin, is simply, a subdivision of the intensity scale For example, if we are working with uint8 images and... of improving the local contrast of an image without altering the global contrast  This method is especially useful in images having large regions of similar tone such as an image with a very light background and dark foreground  Histogram equalization can expose hidden details in an image by stretching out the contrast of local regions and hence making the differences in the region more pronounced... the image with values in the interval [0,127], and h(2) equal to the number of pixels with values in the interval [128 255] Histogram in MATLAB  We obtain the normalized histogram simply by using the expression p = imhist (f, b) / numel(f) numel (f): a MATLAB function that gives the number of elements in array f (i.e the number of pixels in an image Other ways to display Histograms  Consider an image. .. output specified: >> imhist (f); Figure 3.7(a) shows the result 1 Phấn vùng dựa vào sự tương tự vềềcường độ Kỹ thuật 1: Đặt ngưỡng (thresholding)  Ngưỡng đơn  Đa ngưỡng Tài liệu tham khảo  Biomedical image analysis