International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 02 | Feb -2017
p-ISSN: 2395-0072
www.irjet.net
Survey on Image Integration of Misaligned Images Kochurani John1, Andrews Jose2 1PG
student, Dept. of Computer Engineering, VJCET, Vazhakulam, Kerala, India
2Assistant
Professor, Dept. of Computer Engineering, VJCET, Vazhakulam, Kerala, India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Under low lighting conditions the amount of
Recovering a high quality image from a very noisy image is no easy task as fine image details and textures are concealed in noise.
light captured by a camera sensor is often inadequate for recording an image with a clear contrast. Taking satisfactory photos under low lighting conditions using a hand-held camera is a challenging task. Often the photos taken are blurred or noisy. Blurring and imperfection of image due to noise is a common artifact that produces disappointing distorted images with inevitable information loss. There are different methods available for image integration. Most of the previous methods uses well aligned images for integration. In case of misaligned images, the image integration and color transfer yield an unnatural image with low contrast.
Image restoration from a very noisy or blurred image remains a challenging problem. One simple but efficient approach is to use multiple images. Many papers discuss significant improvement in image quality by using flash images. In some previous methods, they combine the features of the images to integrate the colorfulness of a noflash image with the vivid contrast of flash image. Some of these methods have sufficient deblurring or denoising capabilities especially under dim lighting conditions, but they does not handles misaligned images, it require perfectly aligned images. This is a severe restriction in practical use, since a camera needs to be fixed on a tripod, and a scene must be stationary.
Key Words: Image Registration, Image Alignment, Correspondence Algorithm, Image Integration, Color Transfer.
1. INTRODUCTION
2. LITERATURE SURVEY
A blurred or a very noisy image can be reconstructed into a high quality image using Image integration technique. Capturing photos under low light using hand-held cameras will be often unsatisfactory. Such photos might be blurred or noisy.
In [1] Sunghyun Cho and Seungyong Lee proposed a fast deblurring from a single image within a few seconds. The high speed of this method is enabled by accelerating both kernel estimation and latent image estimation steps in the iterative process. Introduce a novel prediction step into the iterative deblurring process where the strong edges are predicted. Image derivatives are used to optimize the function for kernel estimation thus it improves the numerical process by decreasing the number of fourier transforms. A motion blur is a common artifact that produces disappointing blurry images with unavoidable information loss. It is caused by the nature of imaging sensors. During exposure, if the camera sensor moves, a motion blurred image will be obtained. Reconstructing a high quality image from a single image is a challenging task.
The brightness of the image can be increased in three ways. First method is by reducing the shutter speed. But with a shutter speed below a safe range, images may get blurred due to camera shake. Second, is by using a large aperture. A large aperture will however reduce the depth of field. Moreover, the range of apertures in many cameras is very limited. Third is by setting a high ISO. But, as the camera gain is amplified, the noise also may get increased. The largest aperture, safe shutter speed, and the highest ISO are the best settings to take a sharp image in a low light. Even with this combination, the captured image may still be dark and very noisy. Typically, two kinds of degraded image can be taken in the low light. One is a blurred image which is taken with a slow shutter speed and a low ISO setting. Inspite of enough light, correct color, intensity and a high Signal-Noise Ratio (SNR), the image is blurry due to camera shake. The other is an underexposed and noisy image with has a fast shutter speed and also has a high ISO setting. Due to insufficient exposure and high camera gain the image is sharp but very noisy. Due to low contrast the colors of the image are also partially lost.
Š 2017, IRJET
|
Impact Factor value: 5.181
Fig -1: Overview of deblurring process [1]. In [2] Rob Fergus, Barun Singh, Aaron Hertzmann, Sam T. Roweis proposed a conventional blind deconvolution technique to remove the effects of camera shake from
|
ISO 9001:2008 Certified Journal
|
Page 578