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    <title>topic Re: image statistics in Intel® Integrated Performance Primitives</title>
    <link>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976076#M20989</link>
    <description>&lt;P&gt;Hi,&lt;/P&gt;
&lt;P&gt;You can use ippiConvert_8u16u and ippiSqr_16u_C3 to get pixel squares. 3-channel image can be treated as 1-channel image of the same depth, roi.width should be tripled in this case.&lt;/P&gt;
&lt;P&gt;AK&lt;/P&gt;</description>
    <pubDate>Thu, 15 Sep 2005 20:56:38 GMT</pubDate>
    <dc:creator>Intel_C_Intel</dc:creator>
    <dc:date>2005-09-15T20:56:38Z</dc:date>
    <item>
      <title>image statistics</title>
      <link>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976072#M20985</link>
      <description>&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;Hello,&lt;BR /&gt;&lt;BR /&gt;I am writing a background subtraction algorithm. I have 8u_C3 images as input, and I have the need to keep track of the square of these images. Thus I need to keep track of values that range from 0..65536. Should I be using 16u_C3 images to store the square of the image. I could convert the original image to 16u_C3 and then square it. As I understand, 16u_C3 is actually a 5-5-6 bit image, so I do not think that is what I need. I also need all the precision and do not want to use integer scaling. I also would like to avoid going to float images, and sticking with 16 bit per channel images. Is there even such a capability in IPP. If not, this type of functionality would be useful for computer vision.&lt;BR /&gt;&lt;BR /&gt;Thanks. &lt;/DIV&gt;</description>
      <pubDate>Tue, 13 Sep 2005 22:59:01 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976072#M20985</guid>
      <dc:creator>jeff_macdonald</dc:creator>
      <dc:date>2005-09-13T22:59:01Z</dc:date>
    </item>
    <item>
      <title>Re: image statistics</title>
      <link>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976073#M20986</link>
      <description>&lt;DIV&gt;Hi,&lt;/DIV&gt;
&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;16u_C3 is not 5-6-5 format, it is 16-16-16 format, so probably you have necessary precision, right?&lt;/DIV&gt;
&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;Regards,&lt;/DIV&gt;
&lt;DIV&gt; Vladimir&lt;/DIV&gt;</description>
      <pubDate>Tue, 13 Sep 2005 23:48:34 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976073#M20986</guid>
      <dc:creator>Vladimir_Dudnik</dc:creator>
      <dc:date>2005-09-13T23:48:34Z</dc:date>
    </item>
    <item>
      <title>Re: image statistics</title>
      <link>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976074#M20987</link>
      <description>&lt;DIV&gt;Hi, I have a related question that is relevant to background subtraction. There is a lot of functionality available for 16s_C3, but not 16u_C3. Some examples include MulC, AddC. Fot MulC and AddC, what scenarios can you use 16s_C3 on16u_C3 data and expect correct results?&lt;/DIV&gt;
&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;A second issue is that AddWeighted only works on one channel images. Is it possible to treat a 3 channel image as a 1 channel image? This would require constructing a mask that is 3x as large I think. &lt;/DIV&gt;
&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;Thank you!&lt;/DIV&gt;
&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;&lt;/DIV&gt;</description>
      <pubDate>Wed, 14 Sep 2005 00:47:27 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976074#M20987</guid>
      <dc:creator>jpritts</dc:creator>
      <dc:date>2005-09-14T00:47:27Z</dc:date>
    </item>
    <item>
      <title>Re: image statistics</title>
      <link>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976075#M20988</link>
      <description>&lt;DIV&gt;Hi,&lt;/DIV&gt;
&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;you are right, there is some lack of 16u data support in ippIP component. And this is a resource question. Surely we can implement everything in single product, but of course it takes time and each new feature of course is a subject of prioritization. In this particular case, we already have similar functionality in ippSP component, so you can process two-dimensional images on row-by-row basis. And because of that it is in low priority to spend time for developemnt 2-D versions of these functions in ippIP component.&lt;/DIV&gt;
&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;I think you are right, you should be able to use AddWeighted function on C3 image with using mask.&lt;/DIV&gt;
&lt;DIV&gt;&lt;/DIV&gt;
&lt;DIV&gt;Regards,&lt;/DIV&gt;
&lt;DIV&gt; Vladimir&lt;/DIV&gt;</description>
      <pubDate>Wed, 14 Sep 2005 15:40:15 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976075#M20988</guid>
      <dc:creator>Vladimir_Dudnik</dc:creator>
      <dc:date>2005-09-14T15:40:15Z</dc:date>
    </item>
    <item>
      <title>Re: image statistics</title>
      <link>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976076#M20989</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;
&lt;P&gt;You can use ippiConvert_8u16u and ippiSqr_16u_C3 to get pixel squares. 3-channel image can be treated as 1-channel image of the same depth, roi.width should be tripled in this case.&lt;/P&gt;
&lt;P&gt;AK&lt;/P&gt;</description>
      <pubDate>Thu, 15 Sep 2005 20:56:38 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Integrated-Performance/image-statistics/m-p/976076#M20989</guid>
      <dc:creator>Intel_C_Intel</dc:creator>
      <dc:date>2005-09-15T20:56:38Z</dc:date>
    </item>
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