INTERNATIONAL JOURNAL OF PROFESSIONAL ENGINEERING …ijpres.com/pdf12/9.pdf · sharpness, noise...

INTERNATIONAL JOURNAL OF PROFESSIONAL ENGINEERING STUDIES Volume IV /Issue4 / DEC 2014

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A NOVEL APPROACH FOR POWER-CONSTRAINED CONTRAST

ENHANCEMENT FOR EMISSIVE DISPLAYS BASED ON LHM

TALIKOTI.SRAVANI (PG Scholar) 1

J.ANUSHA M.tech 2

1Department of ECE, Rajeev Gandhi Memorial College of Engineering and Technology

2Assistant Professor, 1Department of ECE, Rajeev Gandhi Memorial College of Engineering and Technology

ABSTRACT The proposed work presents a power-constrained contrast-enhancement algorithm for emissive displays based on histogram equalization (HE). To reduce the overstretching artifacts of the conventional HE log-based histogram is applied. Power-consumption model is developed for emissive displays and formulate an objective function that contain power term and histogram-equalizing term. Proposed algorithm provides contrast enhancement and power saving. Proposed algorithm is extend to enhance video sequences, as well as still images contrast and perceptual quality. Index Terms Contrast enhancement, emissive displays, histogram equalization (HE), histogram modification (HM), image enhancement, low-power image processing. I.INTRODUCTION Due to the rapid development in the imaging technology has made easier to take and process digital photographs. We often need only low contrast image only because the lightning condition and imaging systems are not ideal. Image is enhanced by improving many factors such as sharpness, noise level, color accuracy, and contrast. High contrast is an important quality factor for provides better experience of image perception to viewer. Various contrast-enhancement techniques have been developed. For exampled, histogram equalization (HE) is widely used to enhance low-contrast images [1].

Contrast-enhancement techniques have been introduced to improve the qualities of general images, relatively little efforts has been made to adapt the enhancement, process to the characteristics of display devices. In contrast enhancement power saving is also an important issue in various multimedia devices, such as mobile phones and television but displays consume more power in such devices [2],[3]. This trends expect to continue as display size are getting larger. It is required to design a image processing algorithm, which is capable of saving power in

display panels, as well as enhancing image contrast.

Power-constrained contrast-enhancement (PCCE) algorithm is designed, and different characteristics of display panels should be taken into account. Modern display panels can be divided into emissive displays and non emissive displays [4]. Cathode-ray tubes, plasma display panels (PDPs), field emissive displays, and organic light - emitting diode (OLED) are emissive displays that do not required external light sources. Whereas thin-film transistor liquid crystal display (TFT-LCD) is a non emissive one. Emissive displays have several advantages over non emissive ones, including high contrast and low-power consumption.

Emissive display can turn off individual pixels to

obtain high contrast ratio and complete darkness. As the each pixel can be individually driven thus the power consumption by them is very less and it is proportional to they intensity level. Thus OLED and FED are considered as the promising candidates for the next generation display. OLED is consider as the most efficient emissive device in terms of power consumption [5]. OLED is mainly used for the mobile devices, its mass-production technology is being rapidly developed and large OLED panels will be adopted in wider range of device, including televisions and computer monitors [6],[7]. In [8] Choi et al increased pixel values to satisfy the brightness losses caused by reduced backlight intensity. In [2] cheng et al abbreviates both the ends of an image histogram. Then stretched pixel intensities, and Iranli et al [9] employed HE. Tsai et al [3] decomposed an image into high-and low-frequency components. Contrast enhancement and brightness compensation is applied in the subbands of the images. These techniques have been devised for TFT-LCDs only and cannot be employed for emissive displays, in which

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power consumption is affected by pixel values directly, rather than by backlight intensity. PCCE algorithm is proposed for the emissive displays based on the HE. Histogram value is reduced in the histogram modification (HM) scheme to alleviate the contrast overstretching of the conventional HE technique. Power consumption model for emissive displays and formulate an objective function, consisting of the histogram –equalizing term and the power term. Convex optimization techniques are employed to decrease the objective function. Simulation result shoes that the proposed algorithm provides a high image contrast and better perceptual quality while reducing power consumption.

The rest of the paper is designed as follows : Conventional HE and HM technique and proposes a log based HM (LHM) scheme is described in section II. Section III employed with power consumption model for the emissive displays and proposed the PCCE algorithm. Section IV provides the description about how the PCCE algorithm can be extended to increases video sequence. Section V shows the experimental result. Finally, Section VI concludes this paper. II. HE TECHNIQUES HE is one of the most adopted approaches to enhance low-contrast images, which makes the histogram of the light intensities of pixels within an image as uniform as possible [1]. It enhances the dynamic range of an image by deriving a transformation function adaptively. A variety of HE techniques have been presented in [10]-[17]. The proposed PCCE algorithm adopts the HE for its simplicity and effectiveness. Here, we describe conventional HE and HM techniques and then develop an LHM scheme, on which the proposed algorithm is based.

A. HE

In Histogram Equalization pixel intensity is obtained from the input image. Column vector of the histogram is given as h, whose k th element is given as denotes the number of pixel with intensity k.

The probability mass function of intensity k is

estimated by dividing by the total number of pixels in the image. It can be given as

slope. From (4) that the transformation function has sharp

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transition between and when or equivalently, is large. This cause contrast overstretching, mood alteration, or contour artifacts in the output image. Second particularly for dark images, HE transform from low intensities to brighter intensities, which boost noise components as well, degrading the resulting image quality. Third level of contrast enhancement cannot be controlled because the conventional HE is a fully automatic algorithm without parameter. To overcome this drawback, many techniques have been proposed. One of those is HM. HM is the technique that employs the histogram information in an input image to be obtain the transformation function [18], [19]. HE can be regarded as the special case of the HM. In [16],[17] modified the input histogram before the HE procedure to reduce slopes in the transformation function, instead of the direct control of the histogram.

C LHM

HM scheme using logarithm function is developed monotonically increased and can be reduced to large value effectively. Drago et al in [20] establish the logarithm function can successfully decreases the dynamic ranges of high-dynamic–range images while preserving the details. We apply this algorithm to the HM scheme which is called LHM. Logarithm function is to convert the input histogram value to a modified histogram value :

becomes a constant regardless of making the modified histogram uniform. In this way smaller result in the stronger HM. Figure 1(a) shows how to present the LHM scheme modifies an input histogram. According to parameter and Figure. 1(b) plots the corresponding transformation functions, which are obtained by solving (8). In this test, the "Door" image in Figure.1(c) is used as the input image. LHM reduced the reduced the large peak of the input histogram around the pixel values of 70 and thus relaxes the steep slope

(a)

(b)

(c)

(d)

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Figure.2. Flow diagram of the proposed PCCE algorithm

A. Power Model for Emissive Displays

Power consumption in an emissive display panel is modeled which is required to display an image.

Dong et al in [22] proposed a pixel-level power model for an OLED module. Experimental

Output Image

Input Image

Histogram

Acquisition

LHM Formulation of Objective Function

Pixel Mapping

Iterative Optimization

h

m y x

Convex Optimization

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the output image. PCCE algorithm can be employed for any values and provides the optimal transformation function which satisfies all the constraints.

Original Image

PCCE output

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PSNRPC = 33.7509

PSNRLHM = 19.9822

PSNRHE = 8.6648

LHM output

HE output

Original Image

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PCCE output at mu =2

0 50 100 150 200 250 3003.2

3.4

3.6

3.8

4

4.2

4.4

4.6

4.8

5x 10

-3 Histogram analysis at mu = 2

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0 50 100 150 200 250 3002

2.5

3

3.5

4

4.5

5

5.5

6

6.5x 10

-3 Histogram analysis at mu = 5


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0 50 100 150 200 250 3000

0.002

0.004

0.006

0.008

0.01

0.012

0.014Histogram analysis at mu = 7

PCCE output at bet =0

PCCE output at bet =0.5

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TDPPout = 1.0e+12 * 2.5646 (0) 2.1095(0.5) 1.4306(3) 1.4507(2.84)

TDPPin = 2.5740e+12

CONCLUSION

A novel algorithm for emissive displays is proposed in this paper which can enhance image contrast and reduce power

consumption. We have made a power-consumption model and have formulated an objective function, which consists of

the histogram-equalizing term and the power term. Proposed algorithm provides contrast enhancement and power

saving. Proposed algorithm is extending to enhance video sequences, as well as still images contrast and perceptual quality.

PCCE output at bet =3

PCCE output at bet =2.84

0 50 100 150 200 250 3000

50

100

150

200

250

300

Input pixel value

xk

bet=0.5bet=1bet=2.84

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REFERENCES [1] R. C. Gonzalez and R. E. Woods, Digital Image Processing, 3rd ed. Upper Saddle River, NJ: Prentice-Hall, 2007.

[2] W.-C. Cheng, Y. Hou, and M. Pedram, “Power minimization in a backlit TFT-LCD display by concurrent brightness and

contrast scaling,” IEEE Trans. Consum. Electron., vol. 50, no. 1, pp. 25–32, Feb. 2004.

[3] P.-S. Tsai, C.-K. Liang, T.-H. Huang, and H. H. Chen, “Image enhancement for backlight-scaled TFT-LCD displays,”

IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 4, pp. 574–583, Apr. 2009.

[4] W. Den Boer, Active Matrix Liquid Crystal Displays. Amsterdam, The Netherlands: Newnes, 2005.

[5] S. R. Forest, “The road to high efficiency organic light emitting devices,” Org. Electron., vol. 4, no. 2/3, pp. 45–48, Sep.

2003.

[6] B. Young, “OLEDs—Promises, myths, and TVs,” Inf. Display, vol. 25, no. 9, pp. 14–17, Sep. 2009.

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[8] I. Choi, H. Shim, and N. Chang, “Low-power color TFT LCD display for hand-held embedded systems,” in Proc. Int.

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[9] A. Iranli, H. Fatemi, and M. Pedram, “HEBS: Histogram equalization for backlight scaling,” in Proc. Des. Autom. Test

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[11] J.-Y. Kim, L.-S. Kim, and S.-H. Hwang, “An advanced contrast enhancement using partially overlapped sub-block

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[12] Z. Yu and C. Bajaj, “A fast and adaptive method for image contrast enhancement,” in Proc. IEEE ICIP, Oct. 2004, vol.

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[13] T. K. Kim, J. K. Paik, and B. S. Kang, “Contrast enhancement system using spatially adaptive histogram equalization

with temporal filtering,” IEEE Trans. Consum. Electron., vol. 44, no. 1, pp. 82–87, Feb. 1998.

[14] Y.-T. Kim, “Contrast enhancement using brightness preserving bi-histogram equalization,” IEEE Trans. Consum.

Electron., vol. 43, no. 1, pp. 1–8, Feb. 1997.

[15] Y.Wang, Q. Chen, and B. Zhang, “Image enhancement based on equal area dualistic sub-image histogram equalization

method,” IEEE Trans. Consum. Electron., vol. 45, no. 1, pp. 68–75, Feb. 1999.

[16] Q. Wang and R. K. Ward, “Fast image/video contrast enhancement based on weighted thresholded histogram

equalization,” IEEE Trans. Consum. Electron., vol. 53, no. 2, pp. 757–764, May 2007.

[17] T. Arici, S. Dikbas, and Y. Altunbasak, “A histogram modification framework and its application for image contrast

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