Updated detect more loop closures with optimization check to accept (like in dbviewer). DBViewer: added Depth image edition dialog. GainCompensator: now doing it on 3 channels separatly. Export: removed gain's alpha option, added max polygons option, added brightness/contrast auto balance option

corelib/src/util2d.cpp

@@ -1909,6 +1909,89 @@ cv::Mat fastBilateralFiltering(const cv::Mat & depth, float sigmaS, float sigmaR
 	return output;
 }
 
+/**
+ *  \brief Automatic brightness and contrast optimization with optional histogram clipping
+ *  \param [in]src Input image GRAY or BGR or BGRA
+ *  \param [out]dst Destination image
+ *  \param clipHistPercent cut wings of histogram at given percent typical=>1, 0=>Disabled
+ *  \note In case of BGRA image, we won't touch the transparency
+ *  See http://answers.opencv.org/question/75510/how-to-make-auto-adjustmentsbrightness-and-contrast-for-image-android-opencv-image-correction/
+*/
+cv::Mat brightnessAndContrastAuto(const cv::Mat &src, const cv::Mat & mask, float clipLowHistPercent, float clipHighHistPercent)
+{
+
+    CV_Assert(clipLowHistPercent >= 0 && clipHighHistPercent>=0);
+    CV_Assert((src.type() == CV_8UC1) || (src.type() == CV_8UC3) || (src.type() == CV_8UC4));
+
+    int histSize = 256;
+    float alpha, beta;
+    double minGray = 0, maxGray = 0;
+
+    //to calculate grayscale histogram
+    cv::Mat gray;
+    if (src.type() == CV_8UC1) gray = src;
+    else if (src.type() == CV_8UC3) cvtColor(src, gray, CV_BGR2GRAY);
+    else if (src.type() == CV_8UC4) cvtColor(src, gray, CV_BGRA2GRAY);
+    if (clipLowHistPercent == 0 && clipHighHistPercent == 0)
+    {
+        // keep full available range
+        cv::minMaxLoc(gray, &minGray, &maxGray, 0, 0, mask);
+    }
+    else
+    {
+        cv::Mat hist; //the grayscale histogram
+
+        float range[] = { 0, 256 };
+        const float* histRange = { range };
+        bool uniform = true;
+        bool accumulate = false;
+        calcHist(&gray, 1, 0, mask, hist, 1, &histSize, &histRange, uniform, accumulate);
+
+        // calculate cumulative distribution from the histogram
+        std::vector<float> accumulator(histSize);
+        accumulator[0] = hist.at<float>(0);
+        for (int i = 1; i < histSize; i++)
+        {
+            accumulator[i] = accumulator[i - 1] + hist.at<float>(i);
+        }
+
+        // locate points that cuts at required value
+        float max = accumulator.back();
+        clipLowHistPercent *= (max / 100.0); //make percent as absolute
+        clipHighHistPercent *= (max / 100.0); //make percent as absolute
+        // locate left cut
+        minGray = 0;
+        while (accumulator[minGray] < clipLowHistPercent)
+            minGray++;
+
+        // locate right cut
+        maxGray = histSize - 1;
+        while (accumulator[maxGray] >= (max - clipHighHistPercent))
+            maxGray--;
+    }
+
+    // current range
+    float inputRange = maxGray - minGray;
+
+    alpha = (histSize - 1) / inputRange;   // alpha expands current range to histsize range
+    beta = -minGray * alpha;             // beta shifts current range so that minGray will go to 0
+
+    UINFO("minGray=%f maxGray=%f alpha=%f beta=%f", minGray, maxGray, alpha, beta);
+
+    cv::Mat dst;
+    // Apply brightness and contrast normalization
+    // convertTo operates with saurate_cast
+    src.convertTo(dst, -1, alpha, beta);
+
+    // restore alpha channel from source
+    if (dst.type() == CV_8UC4)
+    {
+        int from_to[] = { 3, 3};
+        cv::mixChannels(&src, 4, &dst,1, from_to, 1);
+    }
+    return dst;
+}
+
 }
 
 }