Research On Key Techniques Of Image Enhancement And Its Applications

Image enhancement processing is related with a series of techniques to improveinformation of the focused region, weaken or remove the unnecessary information, oreven to convert the whole image into more suitable information model for human andmachine post-processing such as perception, analysis and recognition in the specialapplication fields. The design of the image enhancement algorithms is focused on thespecial goal of the application. The more requirements for higher quality images in suchimage applications have increased rapidly with the deeper development and widerapplications of the multimedia technologies and products. However, the visual effect ofthe image is affected by many internal and external conditions with the digital imagecapture device, dynamic range in the scenes and light condition. Sometimes thedegraded image is even hard to recognize for human and machine analysis. In order toobtain high quality images do with the processing of the image dynamic rangeadjustment, contrast stretch, color image enhancement and visual perceptionconsistency.Several theoretical methods and techniques of image enhancement are deeplystudied in the dissertation which based on the requirements of the special applications.And further improved algorithms are proposed in the dissertation by analysis of theirproblems and disadvantages in image processing applications. The main work of thedissertation includes enhancement of the color image itself, multi-exposure imagesfusion enhancement based on image domain, and multi-sense images fusionenhancement based on frequency domain.The main innovation of the dissertation:1. A true color image enhancement method is proposed based on the improvementof the visual perception with the tone mapping operation. The proposed methodimprove the contrast of the image adaptively by modified the S-shaped function to suitfor human eye percepts the image in global or local scene information. We firstlyconvert the original image from RGB color space into La*b*color space and do theenhancement in the luminance channel, and in the end combined with the chromaticinformation to overcome the color distortion and unnatural color perception effectsintroduced by the image processing directly in the RGB three channels. Colorconsistency maintaining and achieving adaptive fast image enhancement effects are provided in the resulting images by the proposed algorithm.2. A fast image enhancement method which combined Retinex theory and geneticalgorithm optimization is proposed for color image enhancement. The proposed methodcan disregard the shortcomings introduced by application the traditional imageenhancement methods on gray-scale image expand directly to color image enhancement.So use the Retinex method to decompose the brightness and refection information andapply the genetic algorithm optimization corresponding parameters to enhance theimage brightness information. Finally the proposed method compared with the othermethods in the enhanced result color images is more effective and robust for colorimage enhancement.3. A high dynamic range (HDR) imaging method is proposed by usingmulti-exposure images fusion on their gradient domain information. The proposedmethod takes advantage of the gradient indicates the significant information andneighbor pixels relationship among the multi images in order to design a better weightmatrix for improving visual quality of the fusion image, and overcome the loss ofdetails and fuzzy effects from the conventional weight-averaged methods, finallyacquires an enhanced image with details both improved in brighter and darker regions.4. A free of ghost multi-exposure fusion method is proposed based on image block.The key issue in the processing of multi-exposure fusion image enhancement indynamic scenes is how to remove the ghost due to the movement. The method based ongradient-ascent optimization perform appropriate block, and combine morphologicalopen/close operations, gradient magnitude and gradient direction relative differencebuild objective function for removing ghost. Then fusion image is filtered byGaussian-center blend function to smooth the block boundary artifacts.5. An image enhanced method based on dual-transform is proposed for visualimage and infrared (IR) image fusion. The method based on the secondgenerated-Curvelet and Harr wavelet transform acquired the fusion weight coefficient toeffectively preserve edge and details information in the images for visual and IR imageswith poor-light condition and targets camouflaged in the scenes. The enhanced resultsboth provide more clear space environment for target localization and better visualperception for target recognition.