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In real-time, the images captured are not always appreciable for visual perception.The quality of the image relies on the illumination condition. Contrast enhancement is required to improve the visual quality of the image. In this article, the image enhancement techniques that are adaptable for real-time images are studied. Further, an investigation is done on implementing the image processing algorithms in very large-scale integration (VLSI) hardware. As the image data are comparatively larger, the computational complexity and the memory requirement are more. From the study, the need for efficient computation of such image processing algorithms is realized. The efficient computation of image processing algorithms on hardware platforms, in particular on field programmable gate array (FPGA), is reviewed. As an experiment, the gamma-transformation technique used for image enhancement is realized. Initially, the prototype is modeled using MATLAB, and then it is implemented using an FPGA. K E Y W O R D Sfield programmable gate array, floating point multiplier, image enhancement INTRODUCTIONIn the modern digital world, all multimedia transactions require good-quality images. The visibility of an image depends on the illuminance and reflectance of the scene in the real world. The brightness of a point in an image is non-linear to the brightness of the same point in the real world.Generally, lighting condition determines the quality of an image. The images taken under poor lighting conditions may cause discomfort while viewing images.The image acquired can be degraded due to various reasons such as sensor level malfunction, low visibility, excessive exposure, foggy conditions, and so on. 1 To overcome the degradation, pre-processing is required to enhance the image. Image enhancement is the process of adjusting digital images so that the results are more suitable for display or further processing. It includes processes like deblurring, noise removal, filtering, and so on.Not all images will require the same image enhancement technique because there may be over-exposed regions in outdoor images that will need different treatment compared to indoor images. In literature, there are many algorithms proposed for image enhancement. The technique of being applied for enhancement depends on the input quality of the image. The quality needs to be assessed before applying any approach for a better perception of the image. A real-time implementation of image enhancement is hard to design using software because a large data set is required to represent an image. Since field programmable gate arrays (FPGAs) could exploit the spatial parallelism in image enhancement algorithms they are widely used for hardware implementation.Realizing the design on FPGAs, offer a compromise between the flexibility of general-purpose processors and the hardware-based speed of an integrated-circuit design. 2 Also, the programmable property of FPGA makes them a good choice for image processing applications, as the processing of the number of images also...
In real-time, the images captured are not always appreciable for visual perception.The quality of the image relies on the illumination condition. Contrast enhancement is required to improve the visual quality of the image. In this article, the image enhancement techniques that are adaptable for real-time images are studied. Further, an investigation is done on implementing the image processing algorithms in very large-scale integration (VLSI) hardware. As the image data are comparatively larger, the computational complexity and the memory requirement are more. From the study, the need for efficient computation of such image processing algorithms is realized. The efficient computation of image processing algorithms on hardware platforms, in particular on field programmable gate array (FPGA), is reviewed. As an experiment, the gamma-transformation technique used for image enhancement is realized. Initially, the prototype is modeled using MATLAB, and then it is implemented using an FPGA. K E Y W O R D Sfield programmable gate array, floating point multiplier, image enhancement INTRODUCTIONIn the modern digital world, all multimedia transactions require good-quality images. The visibility of an image depends on the illuminance and reflectance of the scene in the real world. The brightness of a point in an image is non-linear to the brightness of the same point in the real world.Generally, lighting condition determines the quality of an image. The images taken under poor lighting conditions may cause discomfort while viewing images.The image acquired can be degraded due to various reasons such as sensor level malfunction, low visibility, excessive exposure, foggy conditions, and so on. 1 To overcome the degradation, pre-processing is required to enhance the image. Image enhancement is the process of adjusting digital images so that the results are more suitable for display or further processing. It includes processes like deblurring, noise removal, filtering, and so on.Not all images will require the same image enhancement technique because there may be over-exposed regions in outdoor images that will need different treatment compared to indoor images. In literature, there are many algorithms proposed for image enhancement. The technique of being applied for enhancement depends on the input quality of the image. The quality needs to be assessed before applying any approach for a better perception of the image. A real-time implementation of image enhancement is hard to design using software because a large data set is required to represent an image. Since field programmable gate arrays (FPGAs) could exploit the spatial parallelism in image enhancement algorithms they are widely used for hardware implementation.Realizing the design on FPGAs, offer a compromise between the flexibility of general-purpose processors and the hardware-based speed of an integrated-circuit design. 2 Also, the programmable property of FPGA makes them a good choice for image processing applications, as the processing of the number of images also...
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