Histogram equalization

About: Histogram equalization is a research topic. Over the lifetime, 5755 publications have been published within this topic receiving 89313 citations.

Locally adapted histogram equalization

Abstract: A system and method for improving the uniformity in exposure and tone of a digital image using a locally adapted histogram equalization approach. This approach involves first segmenting the digital image into a plurality of image patches. For each of these patches, a pixel brightness level histogram is created. The histogram for each patch is then optionally averaged with the histograms associated with a prescribed number of neighboring image patches. A normalized cumulative distribution function is generated for each patch based on the associated averaged histogram. This normalized-cumulative distribution function identifies a respective new pixel brightness level for each of the original pixel brightness levels. For each of the original pixel brightness levels, the 1s associated new pixel brightness levels from one or more of the image patches are blended. Preferably, this blending is accomplished using either a bilinear or biquadratic interpolator function. Finally, for each image patch, the original pixel brightness level of each pixel in the image patch is replaced with the blended pixel brightness level corresponding to that original brightness level. A further refinement can also be implemented to mitigate the effects of noise caused by areas of a single color in the scene depicted in patch. In one embodiment, this refinement entails employing a partially equalization approach. In another embodiment, the refinement entails limiting the gain exhibited by any of the blended pixel brightness levels associated with an image patch, in comparison to its associated original pixel brightness level, to a prescribed level.

An advanced contrast enhancement using partially overlapped sub-block histogram equalization

Abstract: In this paper, an advanced histogram equalization algorithm for contrast enhancement is presented. Histogram equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. Global histogram equalization is simple and fast, but its contrast enhancement power is relatively low. Local histogram equalization, on the other hand, can enhance overall contrast more effectively, but the computational complexity is very high due to its fully overlapped sub-blocks. For high contrast and simple calculation, a low pass filter type mask is proposed. The low pass filter type mask is realized by partially overlapped sub-block histogram equalization (POSHE). With the proposed method, the computation overhead is reduced by a factor of about one hundred compared to that of local histogram equalization while still achieving high contrast.

A new histogram equalization method for digital image enhancement and brightness preservation

Abstract: This paper proposes a new histogram equalization method for effective and efficient mean brightness preservation and contrast enhancement, which prevents intensity saturation and has the ability to preserve image fine details. Basically, the proposed method first separates the test image histogram into two sub-histograms. Then, the plateau limits are calculated from the respective sub-histograms, and they are used to modify those sub-histograms. Histogram equalization is then separately performed on the two sub-histograms to yield a clean and enhanced image. To demonstrate the feasibility of the proposed method, a total of 190 test images are used in simulation and comparison, in which 72 of them are standard test images, while the remainder are made up of real natural images obtained from personal digital camera. The simulation results show that the proposed method outperforms other state-of-the-art methods, both in terms of visual and runtime comparison. Moreover, the simple implementation and fast runtime further underline the importance of the proposed method in consumer electronic products, such as mobile cell-phone, digital camera, and video.

A Variational Model for Histogram Transfer of Color Images

Abstract: In this paper, we propose a variational formulation for histogram transfer of two or more color images. We study an energy functional composed by three terms: one tends to approach the cumulative histograms of the transformed images, the other two tend to maintain the colors and geometry of the original images. By minimizing this energy, we obtain an algorithm that balances equalization and the conservation of features of the original images. As a result, they evolve while approaching an intermediate histogram between them. This intermediate histogram does not need to be specified in advance, but it is a natural result of the model. Finally, we provide experiments showing that the proposed method compares well with the state of the art.