Satellite Image Resolution Enhancement Using Complex Wavelet Transform
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 7, NO. 2, APRIL 2010
333
Satellite Image Contrast Enhancement
Using Discrete Wavelet Transform and
Singular Value Decomposition
Hasan Demirel, Cagri Ozcinar, and Gholamreza Anbarjafari
Abstract—In this letter, a new satellite image contrast enhancement technique based on the discrete wavelet transform (DWT) and singular value decomposition has been proposed. The technique decomposes the input image into the four frequency subbands by using DWT and estimates the singular value matrix of the low–low subband image, and, then, it reconstructs the enhanced image by applying inverse DWT. The technique is compared with conventional image equalization techniques such as standard general histogram equalization and local histogram equalization, as well as state-of-the-art techniques such as brightness preserving dynamic histogram equalization and singular value equalization. The experimental results show the superiority of the proposed method over conventional and state-of-the-art techniques. Index Terms—Discrete wavelet transform, image equalization, satellite image contrast enhancement.
I. I NTRODUCTION
S
ATELLITE images are used in many applications such as geosciences studies, astronomy, and geographical information systems. One of the most important quality factors in satellite images comes from its contrast. Contrast enhancement is frequently referred to as one of the most important issues in image processing. Contrast is created by the difference in luminance reflected from two adjacent surfaces. In visual perception, contrast is determined by the difference in the color and brightness of an object with other objects. Our visual system is more sensitive to contrast than absolute luminance; therefore, we can perceive the world similarly regardless of the considerable changes in illumination conditions.
If the contrast of an image is highly concentrated on a specific range, the
333
Satellite Image Contrast Enhancement
Using Discrete Wavelet Transform and
Singular Value Decomposition
Hasan Demirel, Cagri Ozcinar, and Gholamreza Anbarjafari
Abstract—In this letter, a new satellite image contrast enhancement technique based on the discrete wavelet transform (DWT) and singular value decomposition has been proposed. The technique decomposes the input image into the four frequency subbands by using DWT and estimates the singular value matrix of the low–low subband image, and, then, it reconstructs the enhanced image by applying inverse DWT. The technique is compared with conventional image equalization techniques such as standard general histogram equalization and local histogram equalization, as well as state-of-the-art techniques such as brightness preserving dynamic histogram equalization and singular value equalization. The experimental results show the superiority of the proposed method over conventional and state-of-the-art techniques. Index Terms—Discrete wavelet transform, image equalization, satellite image contrast enhancement.
I. I NTRODUCTION
S
ATELLITE images are used in many applications such as geosciences studies, astronomy, and geographical information systems. One of the most important quality factors in satellite images comes from its contrast. Contrast enhancement is frequently referred to as one of the most important issues in image processing. Contrast is created by the difference in luminance reflected from two adjacent surfaces. In visual perception, contrast is determined by the difference in the color and brightness of an object with other objects. Our visual system is more sensitive to contrast than absolute luminance; therefore, we can perceive the world similarly regardless of the considerable changes in illumination conditions.
If the contrast of an image is highly concentrated on a specific range, the