The contrast of any image is a very important characteristic by which the image can be judged as good or poor. In this paper, we introduce a simple approach for the process of image contrast enhancement using the sigmoid function in spatial domain. To achieve this simple contrast enhancement, a novel mask based on using the input value together with the sigmoid function formula in an equation that will be used as contrast enhancer. This new contrast enhancer is passing over the target image, operates on its pixels, one by one. The new contrast enhancer is a scaled version of the input that is performed by applying a sigmoid function to the signal itself. The intensity value of each pixel in the output image is computing according to a specific formula. The parameters of the sigmoid function were determined by using three different methods. The effect of gain's value on the contrast enhancement process was studied. The new enhancing approach has been successfully, applied in several gray scale images. We proved that it works efficiently in different dark and bright images adjusting their contrasts. Moreover, the new enhancing approach was effective in dealing with colored images resulting in high-quality outputs. Our proposed algorithm is a simple approach that can be used successfully, in various applications suffering from different image's contrast problems.

The contrast of any image is a very important characteristic by which the image can be judged as good or poor. In this paper, we introduce a simple approach for the process of image contrast enhancement using the sigmoid function in spatial domain. To achieve this simple contrast enhancement, a novel mask based on using the input value together with the sigmoid function formula in an equation that will be used as contrast enhancer. This new contrast enhancer is passing over the target image, operates on its pixels, one by one. The new contrast enhancer is a scaled version of the input that is performed by applying a sigmoid function to the signal itself. The intensity value of each pixel in the output image is computing according to a specific formula. The parameters of the sigmoid function were determined by using three different methods. The effect of gain's value on the contrast enhancement process was studied. The new enhancing approach has been successfully, applied in several gray scale images. We proved that it works efficiently in different dark and bright images adjusting their contrasts. Moreover, the new enhancing approach was effective in dealing with colored images resulting in high-quality outputs. Our proposed algorithm is a simple approach that can be used successfully, in various applications suffering from different image's contrast problems.

The contrast of any image is a very important characteristic by which the image can be judged as good or poor. In this paper, we introduce a simple approach for the process of image contrast enhancement using the sigmoid function in spatial domain. To achieve this simple contrast enhancement, a novel mask based on using the input value together with the sigmoid function formula in an equation that will be used as contrast enhancer. This new contrast enhancer is passing over the target image, operates on its pixels, one by one. The new contrast enhancer is a scaled version of the input that is performed by applying a sigmoid function to the signal itself. The intensity value of each pixel in the output image is computing according to a specific formula. The parameters of the sigmoid function were determined by using three different methods. The effect of gain's value on the contrast enhancement process was studied. The new enhancing approach has been successfully, applied in several gray scale images. We proved that it works efficiently in different dark and bright images adjusting their contrasts. Moreover, the new enhancing approach was effective in dealing with colored images resulting in high-quality outputs. Our proposed algorithm is a simple approach that can be used successfully, in various applications suffering from different image's contrast problems.