Abstract
We present an explicit formula which unifies the mask of -point ternary interpolating as well as approximating subdivision schemes. We observe that the odd point ternary interpolating and approximating schemes introduced by Lian (2009), Siddiqi and Rehan (2010, 2009) and Hassan and Dodgson (2003) are special cases of our proposed masks/schemes. Moreover, schemes introduced by Zheng et al. (2009) can easily be generated by our proposed masks. It is also proved from comparison that -point schemes are better than -scheme in the sense of computational cost, support and error bounds.
1. Introduction
Subdivision is an algorithmic technique to generate smooth curves and surfaces as a sequence of successively refined control polygons. The schemes involving convex combination of more or less than six points at coarse refinement level to insert a new point at next refinement level is introduced by [1–8]. They introduced odd and even points ternary schemes. Zheng et al. [9] constructed -point ternary interpolatory subdivision schemes by using variation of constants. They also introduced ternary even symmetric -point subdivision schemes [10]. Mustafa and Khan [11] presented a new 4-point quaternary approximating subdivision scheme. Lian [12] generalized 3-point and 5-point interpolatory schemes into an -ary subdivision scheme for curve design. Later on, he further generalized his work into -point and -point interpolating -ary schemes for curve design [13]. Mustafa and Najma [14] generalized and unified even-point -ary interpolating and approximating subdivision schemes for any . In this paper, we introduce an explicit formula which generalizes and unifies existing odd-point ternary interpolating and approximating subdivision schemes. A general formula which unifies odd-point and even-point -ary interpolating and approximating schemes is still under investigation.
2. Preliminaries
Let be the set of integers and be the set of constants. A general form of -point ternary subdivision scheme which relates a set of control points to refined set of control points is defined by Which is formally denoted by . The set of constants is called mask of the scheme . A necessary condition for the uniform convergence of the subdivision scheme (2.1) given by [3] is The Laurent polynomial corresponding to the mask of convergent subdivision scheme (2.1) satisfies For the given , we define Lagrange fundamental polynomials of degree , at the points , by and Lagrange fundamental polynomials of degree at the points , by
3. -Point Ternary Approximating and Interpolating Schemes
Here, first we present some preliminary identities then we will offer masks of -point ternary approximating and interpolating schemes.
Lemma 3.1. If is Lagrange fundamental polynomial of degree corresponding to nodes defined by (2.5), then where .
Proof. Consider
This implies
This further implies
This can be written as
where . It is easy to verify that
Now by substituting (3.5), (3.6), and in (2.5), we get (3.1).
This completes the proof.
Similarly, we can prove the following lemma.
Lemma 3.2. If is Lagrange fundamental polynomial of degree corresponding to nodes defined by (2.6) then where .
Lemma 3.3. If and are Lagrange polynomials defined by (2.5) and (3.1), then where .
Proof. By (3.1), for , we get Using (3.1), (3.7), and (3.9), we get (3.8). This completes the proof.
Remark 3.4. In the setting of primal parametrization, each ternary refinement of coarse polygon of scheme (2.1) replaces the old data by new data and , one to the left, the other to the right, and both at one-third the distance to the neighbours and . In other words, ternary refinement (2.1) defines a scheme whereby replaces the value at the mesh point and and are inserted at the new mesh point and , respectively.
Therefore, we can select the value of either or to prove the Lemmas 3.1–3.3. In this paper, has been selected. One can select to proof the above lemmas. The results of the above lemmas at are same but the final mask of the scheme obtained in reverse order. Negative values give a proper order of the mask, that have why negative values have been selected to prove the above lemmas.
Now here we present the masks of -point ternary approximating and interpolating schemes.
Theorem 3.5. An explicit formula for the mask of -point ternary scheme (2.1) is defined by where is free parameter while , , and are defined by (3.7), (3.8), and (3.9) respectively.
3.1. 3-, 5-, 7-Point Ternary Approximating Schemes
Here, we present three special cases of approximating schemes generated by (3.10) with free parameter.(i) If then by (2.1) and (3.10), we get the following 3-point ternary approximating scheme:(ii) If then by (2.1) and (3.10), we get the following 5-point ternary approximating scheme:(iii) If then by (3.10), we get the following mask of 7-point ternary approximating scheme: where
3.2. 3-, 5-Point Ternary Interpolating Schemes
Here, we present two special cases of approximating schemes generated by (3.10) with free parameters.(i) By setting and , we get the following 3-point ternary interpolating scheme:(ii) If and , then by (2.1) and (3.10), we get the following 5-point ternary interpolating scheme:
3.3. Comparison with Existing Ternary Schemes
In this section, we will show that the popular existing odd-point ternary schemes are special cases of our proposed family of scheme. Here we will also compare the error bounds between limit curve and control polygon after -fold subdivision of odd-point and even-point schemes.
3.3.1. Special Cases
Here we see that the most of the existing odd-point ternary subdivision schemes are either special cases or can be obtain by setting free parameter in our proposed masks.(i) By letting in (3.10), Zheng et al. -point interpolating scheme [9] becomes special case of our scheme.(ii) By substituting , and in (3.15) and (3.16), we get 3-point and 5-point ternary interpolating schemes of Lian [12] respectively.(iii) By substituting in (3.13), we get 7-point ternary interpolating scheme of Lian [13]. Similarly, from (3.10), we can generate -point ternary interpolating schemes of [13].(iv) For , and parameter in our proposed mask (3.13), 3-point ternary approximating scheme given in [7] becomes special case of our scheme.(v) For , and in (3.11), we get 3-point approximating scheme of Hassan and Dodgson [4].(vi) For , and in (3.11), we get 3-point interpolating scheme of Hassan and Dodgson [4].
3.3.2. Error Bounds
In Tables 1 and 2 by using [15], with , we have computed error bounds between limit curve and control polygon after -fold subdivision of odd-point and even-point ternary approximating and interpolating schemes. It is clear from Tables 1 and 2 that error bounds of 3-point ternary schemes (3.11) and (3.15) at each subdivision level are less than the error bounds of 4-point ternary schemes [3, 10] at each level. Similarly error bounds of 5-point scheme (3.12) and (3.16) are less than the error bounds of 6-point schemes [10, 16]. Similar results can be obtained by comparing other odd-point and even-point schemes. Graphical representation of error bounds is shown in Figure 1.
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Moreover, support and computational cost of -point schemes are less than -point schemes. Therefore, we conclude that -point schemes are better than -point schemes in the sense of support, computational cost, and error bounds.
3.4. Effects of Parameters in Proposed Schemes
We will discuss three major effects/upshots of parameter in schemes (3.11)–(3.16). Effect of parameters in other schemes can be discuss analogously.
3.4.1. Continuity
The effect/upshots of parameter in schemes (3.11)–(3.16) on order of continuity is shown in Tables 3 and 4. One can easily find the order of continuity over parametric intervals by using approach of [4].
3.4.2. Shapes of Limit Curves
In Figure 2, the effect of parameter in (3.11)–(3.16) on graph and continuity of limit curve is shown. These figures are exposed to show the role of free parameter when 3- and 5-point approximating and interpolating schemes (3.11)–(3.16) applied on discrete data points. From these figures, we see that the behavior of the limiting curve acts as tightness/looseness when the values of free parameter vary.
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3.4.3. Error Bounds
The effects of parameter on error bounds at each subdivision level between th level control polygon and limit curves are shown in Figure 3, Tables 5 and 6. From these tables and figures, we conclude that in case of 3-point approximating scheme continuity is maximum over and error bound is minimum over . On each side of interval continuity decreases while error bounds increases on each side of interval . In case of 5-, 7-point approximating scheme continuity is maximum over and , while error bound is minimum at and , respectively.
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While in case of 3- and 5-point interpolating scheme continuity is maximum over and , while error bound is minimum at and , respectively.
3.5. Conclusion
In this paper, we offered an explicit general formula for the generation of mask of -point ternary interpolating as well as approximating schemes. We have concluded from figures and tables that the -point schemes are better than -point schemes for in the sense of computational cost, support and error bounds. Moreover, odd-point ternary schemes of Hassan and Dodgson [4], Lian [12, 13], Zheng et al. [9], and Siddiqi and Rehan [7, 8] are special cases of our proposed masks.
Acknowledgment
This work is supported by the Indigenous Ph.D. Scholarship Scheme of Higher Education Commission (HEC), Pakistan.